Andrew McCallum

436 papers A* 86A 28B 11Misc 2Journal 156Unranked 149

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Autoregressive Ranking: Bridging the Gap Between Dual and Cross Encoders. CoRR Benjamin Rozonoyer, Chong You, Michael Boratko, Himanshu Jain, Nilesh Gupta, Srinadh Bhojanapalli, Andrew McCallum, Felix Yu
2026	J	`jnl`	Insertion Based Sequence Generation with Learnable Order Dynamics. CoRR Dhruvesh Patel, Benjamin Rozonoyer, Gaurav Pandey, Tahira Naseem, Ramón Fernandez Astudillo, Andrew McCallum
2026	J	`jnl`	PROMPT2BOX: Uncovering Entailment Structure among LLM Prompts. CoRR Neeladri Bhuiya, Shib Sankar Dasgupta, Andrew McCallum, Haw-Shiuan Chang
2026	—	`conf`	xLM: A Python Package for Non-Autoregressive Language Models. EACL (System Demonstrations) Dhruvesh Patel, Durga Prasad Maram, Sai Sreenivas Chintha, Benjamin Rozonoyer, Andrew McCallum
2025	A*	`conf`	A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings. ICML Shib Sankar Dasgupta, Michael Boratko, Andrew McCallum
2025	J	`jnl`	A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings. CoRR Shib Sankar Dasgupta, Michael Boratko, Andrew McCallum
2025	A*	`conf`	Bridging Personalization and Control in Scientific Personalized Search. SIGIR Sheshera Mysore, Garima Dhanania, Kishor Patil, Surya Kallumadi, Andrew McCallum, Hamed Zamani
2025	J	`jnl`	Identity Theft in AI Conference Peer Review. Commun. ACM Nihar B. Shah, Melisa Bok, Xukun Liu, Andrew McCallum
2025	J	`jnl`	Identity Theft in AI Conference Peer Review. CoRR Nihar B. Shah, Melisa Bok, Xukun Liu, Andrew McCallum
2025	J	`jnl`	Insertion Language Models: Sequence Generation with Arbitrary-Position Insertions. CoRR Dhruvesh Patel, Aishwarya Sahoo, Avinash Amballa, Tahira Naseem, Tim G. J. Rudner, Andrew McCallum
2025	J	`jnl`	ML Researchers Support Openness in Peer Review But Are Concerned About Resubmission Bias. CoRR Vishisht Rao, Justin Payan, Andrew McCallum, Nihar B. Shah
2025	J	`jnl`	MiGrATe: Mixed-Policy GRPO for Adaptation at Test-Time. CoRR Peter Phan, Dhruv Agarwal, Kavitha Srinivas, Horst Samulowitz, Pavan Kapanipathi, Andrew McCallum
2025	J	`jnl`	Open-ended Scientific Discovery via Bayesian Surprise. CoRR Dhruv Agarwal, Bodhisattwa Prasad Majumder, Reece Adamson, Megha Chakravorty, Satvika Reddy Gavireddy, Aditya Parashar, Harshit Surana, Bhavana Dalvi Mishra, Andrew McCallum, Ashish Sabharwal, Peter Clark
2025	J	`jnl`	OpenUnlearning: Accelerating LLM Unlearning via Unified Benchmarking of Methods and Metrics. CoRR Vineeth Dorna, Anmol Mekala, Wenlong Zhao, Andrew McCallum, Zachary C. Lipton, J. Zico Kolter, Pratyush Maini
2025	J	`jnl`	XLM: A Python package for non-autoregressive language models. CoRR Dhruvesh Patel, Durga Prasad Maram, Sai Sreenivas Chintha, Benjamin Rozonoyer, Andrew McCallum
2024	A*	`conf`	A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. ICML Nicholas Monath, Will Sussman Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer
2024	J	`jnl`	A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks. CoRR Nicholas Monath, Will Grathwohl, Michael Boratko, Rob Fergus, Andrew McCallum, Manzil Zaheer
2024	A*	`conf`	Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. ICLR Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum
2024	J	`jnl`	Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders. CoRR Nishant Yadav, Nicholas Monath, Manzil Zaheer, Rob Fergus, Andrew McCallum
2024	A*	`conf`	Analysis of Plan-based Retrieval for Grounded Text Generation. EMNLP Ameya Godbole, Nicholas Monath, Seungyeon Kim, Ankit Singh Rawat, Andrew McCallum, Manzil Zaheer
2024	J	`jnl`	Analysis of Plan-based Retrieval for Grounded Text Generation. CoRR Ameya Godbole, Nicholas Monath, Seungyeon Kim, Ankit Singh Rawat, Andrew McCallum, Manzil Zaheer
2024	A*	`conf`	Comparing Neighbors Together Makes it Easy: Jointly Comparing Multiple Candidates for Efficient and Effective Retrieval. EMNLP Jonghyun Song, Cheyon Jin, Wenlong Zhao, Andrew McCallum, Jay-Yoon Lee
2024	—	`conf`	Every Answer Matters: Evaluating Commonsense with Probabilistic Measures. ACL (1) Qi Cheng, Michael Boratko, Pranay Kumar Yelugam, Tim O'Gorman, Nalini Singh, Andrew McCallum, Xiang Li
2024	J	`jnl`	Every Answer Matters: Evaluating Commonsense with Probabilistic Measures. CoRR Qi Cheng, Michael Boratko, Pranay Kumar Yelugam, Tim O'Gorman, Nalini Singh, Andrew McCallum, Xiang Lorraine Li
2024	A*	`conf`	Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching. ICML Rico Angell, Andrew McCallum
2024	J	`jnl`	Incremental Extractive Opinion Summarization Using Cover Trees. CoRR Somnath Basu Roy Chowdhury, Nicholas Monath, Avinava Dubey, Manzil Zaheer, Andrew McCallum, Amr Ahmed, Snigdha Chaturvedi
2024	J	`jnl`	Incremental Extractive Opinion Summarization Using Cover Trees. Trans. Mach. Learn. Res. Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Manzil Zaheer, Andrew McCallum, Amr Ahmed, Snigdha Chaturvedi
2024	J	`jnl`	Interactive Topic Models with Optimal Transport. CoRR Garima Dhanania, Sheshera Mysore, Chau Minh Pham, Mohit Iyyer, Hamed Zamani, Andrew McCallum
2024	A*	`conf`	Learning Representations for Hierarchies with Minimal Support. NeurIPS Benjamin Rozonoyer, Michael Boratko, Dhruvesh Patel, Wenlong Zhao, Shib Sankar Dasgupta, Hung Le, Andrew McCallum
2024	J	`jnl`	Memory Augmented Cross-encoders for Controllable Personalized Search. CoRR Sheshera Mysore, Garima Dhanania, Kishor Patil, Surya Kallumadi, Andrew McCallum, Hamed Zamani
2024	—	`conf`	Multistage Collaborative Knowledge Distillation from a Large Language Model for Semi-Supervised Sequence Generation. ACL (1) Jiachen Zhao, Wenlong Zhao, Andrew Drozdov, Benjamin Rozonoyer, Md. Arafat Sultan, Jay-Yoon Lee, Mohit Iyyer, Andrew McCallum
2024	A	`conf`	To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential Recommenders. WSDM Haw-Shiuan Chang, Nikhil Agarwal, Andrew McCallum
2023	J	`jnl`	Adaptive Selection of Anchor Items for CUR-based k-NN search with Cross-Encoders. CoRR Nishant Yadav, Nicholas Monath, Manzil Zaheer, Andrew McCallum
2023	J	`jnl`	Answering Compositional Queries with Set-Theoretic Embeddings. CoRR Shib Sankar Dasgupta, Andrew McCallum, Steffen Rendle, Li Zhang
2023	—	`conf`	Causal Matching with Text Embeddings: A Case Study in Estimating the Causal Effects of Peer Review Policies. ACL (Findings) Raymond Zhang, Neha Nayak Kennard, Daniel Scott Smith, Daniel A. McFarland, Andrew McCallum, Katherine Keith
2023	J	`jnl`	Editable User Profiles for Controllable Text Recommendation. CoRR Sheshera Mysore, Mahmood Jasim, Andrew McCallum, Hamed Zamani
2023	A*	`conf`	Editable User Profiles for Controllable Text Recommendations. SIGIR Sheshera Mysore, Mahmood Jasim, Andrew McCallum, Hamed Zamani
2023	—	`conf`	Efficient k-NN Search with Cross-Encoders using Adaptive Multi-Round CUR Decomposition. EMNLP (Findings) Nishant Yadav, Nicholas Monath, Manzil Zaheer, Andrew McCallum
2023	J	`jnl`	Encoding Multi-Domain Scientific Papers by Ensembling Multiple CLS Tokens. CoRR Ronald Seoh, Haw-Shiuan Chang, Andrew McCallum
2023	J	`jnl`	Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching. CoRR Rico Angell, Andrew McCallum
2023	A	`conf`	Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining. AISTATS Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew McCallum
2023	J	`jnl`	Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining. CoRR Nicholas Monath, Manzil Zaheer, Kelsey Allen, Andrew McCallum
2023	A*	`conf`	KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. ICLR Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi
2023	—	`conf`	KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. SustaiNLP Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi
2023	A	`conf`	Large Language Model Augmented Narrative Driven Recommendations. RecSys Sheshera Mysore, Andrew McCallum, Hamed Zamani
2023	J	`jnl`	Large Language Model Augmented Narrative Driven Recommendations. CoRR Sheshera Mysore, Andrew McCallum, Hamed Zamani
2023	—	`conf`	Longtonotes: OntoNotes with Longer Coreference Chains. EACL (Findings) Kumar Shridhar, Nicholas Monath, Raghuveer Thirukovalluru, Alessandro Stolfo, Manzil Zaheer, Andrew McCallum, Mrinmaya Sachan
2023	A	`conf`	Low-Resource Compositional Semantic Parsing with Concept Pretraining. EACL Subendhu Rongali, Mukund Sridhar, Haidar Khan, Konstantine Arkoudas, Wael Hamza, Andrew McCallum
2023	J	`jnl`	Low-Resource Compositional Semantic Parsing with Concept Pretraining. CoRR Subendhu Rongali, Mukund Sridhar, Haidar Khan, Konstantine Arkoudas, Wael Hamza, Andrew McCallum
2023	—	`conf`	Machine Reading Comprehension using Case-based Reasoning. EMNLP (Findings) Dung Thai, Dhruv Agarwal, Mudit Chaudhary, Wenlong Zhao, Rajarshi Das, Jay-Yoon Lee, Hannaneh Hajishirzi, Manzil Zaheer, Andrew McCallum
2023	J	`jnl`	Machine Reading Comprehension using Case-based Reasoning. CoRR Dung Thai, Dhruv Agarwal, Mudit Chaudhary, Wenlong Zhao, Rajarshi Das, Manzil Zaheer, Jay-Yoon Lee, Hannaneh Hajishirzi, Andrew McCallum
2023	—	`conf`	Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling. ACL (1) Haw-Shiuan Chang, Ruei-Yao Sun, Kathryn Ricci, Andrew McCallum
2023	J	`jnl`	Multistage Collaborative Knowledge Distillation from Large Language Models. CoRR Jiachen Zhao, Wenlong Zhao, Andrew Drozdov, Benjamin Rozonoyer, Md. Arafat Sultan, Jay-Yoon Lee, Mohit Iyyer, Andrew McCallum
2023	A*	`conf`	Online Level-wise Hierarchical Clustering. KDD Nicholas Monath, Manzil Zaheer, Andrew McCallum
2023	—	`conf`	PaRaDe: Passage Ranking using Demonstrations with LLMs. EMNLP (Findings) Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, Kai Hui
2023	J	`jnl`	PaRaDe: Passage Ranking using Demonstrations with Large Language Models. CoRR Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, Kai Hui
2023	—	`conf`	Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond. ACL (Findings) Haw-Shiuan Chang, Zonghai Yao, Alolika Gon, Hong Yu, Andrew McCallum
2023	J	`jnl`	Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond. CoRR Haw-Shiuan Chang, Zonghai Yao, Alolika Gon, Hong Yu, Andrew McCallum
2023	J	`jnl`	To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential Recommenders. CoRR Haw-Shiuan Chang, Nikhil Agarwal, Andrew McCallum
2022	B	`conf`	A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and Genes. LREC Dongxu Zhang, Sunil Mohan, Michaela Torkar, Andrew McCallum
2022	J	`jnl`	A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and Genes. CoRR Dongxu Zhang, Sunil Mohan, Michaela Torkar, Andrew McCallum
2022	A*	`conf`	An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity. AAAI Siddhartha Mishra, Nicholas Monath, Michael Boratko, Ariel Kobren, Andrew McCallum
2022	J	`jnl`	Augmenting Scientific Creativity with Retrieval across Knowledge Domains. CoRR Hyeonsu B. Kang, Sheshera Mysore, Kevin Huang, Haw-Shiuan Chang, Thorben Prein, Andrew McCallum, Aniket Kittur, Elsa A. Olivetti
2022	J	`jnl`	CBR-iKB: A Case-Based Reasoning Approach for Question Answering over Incomplete Knowledge Bases. CoRR Dung Thai, Srinivas Ravishankar, Ibrahim Abdelaziz, Mudit Chaudhary, Nandana Mihindukulasooriya, Tahira Naseem, Rajarshi Das, Pavan Kapanipathi, Achille Fokoue, Andrew McCallum
2022	—	`conf`	DISAPERE: A Dataset for Discourse Structure in Peer Review Discussions. NAACL-HLT Neha Nayak Kennard, Tim O'Gorman, Rajarshi Das, Akshay Sharma, Chhandak Bagchi, Matthew Clinton, Pranay Kumar Yelugam, Hamed Zamani, Andrew McCallum
2022	A*	`conf`	Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization. EMNLP Nishant Yadav, Nicholas Monath, Rico Angell, Manzil Zaheer, Andrew McCallum
2022	J	`jnl`	Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization. CoRR Nishant Yadav, Nicholas Monath, Rico Angell, Manzil Zaheer, Andrew McCallum
2022	B	`conf`	Enhanced Distant Supervision with State-Change Information for Relation Extraction. LREC Jui Shah, Dongxu Zhang, Sam Brody, Andrew McCallum
2022	—	`conf`	Entity Linking via Explicit Mention-Mention Coreference Modeling. NAACL-HLT Dhruv Agarwal, Rico Angell, Nicholas Monath, Andrew McCallum
2022	—	`conf`	Event-Event Relation Extraction using Probabilistic Box Embedding. ACL (2) Eunjeong Hwang, Jay-Yoon Lee, Tianyi Yang, Dhruvesh Patel, Dongxu Zhang, Andrew McCallum
2022	—	`conf`	Inducing and Using Alignments for Transition-based AMR Parsing. NAACL-HLT Andrew Drozdov, Jiawei Zhou, Radu Florian, Andrew McCallum, Tahira Naseem, Yoon Kim, Ramón Fernandez Astudillo
2022	J	`jnl`	Inducing and Using Alignments for Transition-based AMR Parsing. CoRR Andrew Drozdov, Jiawei Zhou, Radu Florian, Andrew McCallum, Tahira Naseem, Yoon Kim, Ramón Fernandez Astudillo
2022	A*	`conf`	Interactive Correlation Clustering with Existential Cluster Constraints. ICML Rico Angell, Nicholas Monath, Nishant Yadav, Andrew McCallum
2022	A*	`conf`	Knowledge Base Question Answering by Case-based Reasoning over Subgraphs. ICML Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Manzil Zaheer, Hannaneh Hajishirzi, Robin Jia, Andrew McCallum
2022	J	`jnl`	Knowledge Base Question Answering by Case-based Reasoning over Subgraphs. CoRR Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Robin Jia, Manzil Zaheer, Hannaneh Hajishirzi, Andrew McCallum
2022	J	`jnl`	Longtonotes: OntoNotes with Longer Coreference Chains. CoRR Kumar Shridhar, Nicholas Monath, Raghuveer Thirukovalluru, Alessandro Stolfo, Manzil Zaheer, Andrew McCallum, Mrinmaya Sachan
2022	—	`conf`	Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-Learning. AutoML Trapit Bansal, Salaheddin Alzubi, Tong Wang, Jay-Yoon Lee, Andrew McCallum
2022	A*	`conf`	Modeling Label Space Interactions in Multi-label Classification using Box Embeddings. ICLR Dhruvesh Patel, Pavitra Dangati, Jay-Yoon Lee, Michael Boratko, Andrew McCallum
2022	A*	`conf`	Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings. NeurIPS Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum
2022	J	`jnl`	Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling. CoRR Haw-Shiuan Chang, Ruei-Yao Sun, Kathryn Ricci, Andrew McCallum
2022	—	`conf`	Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions. ACL (1) Haw-Shiuan Chang, Andrew McCallum
2022	A*	`conf`	Structured Energy Network As a Loss. NeurIPS Jay Yoon Lee, Dhruvesh Patel, Purujit Goyal, Wenlong Zhao, Zhiyang Xu, Andrew McCallum
2022	A*	`conf`	Sublinear Time Approximation of Text Similarity Matrices. AAAI Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco
2022	—	`conf`	Unsupervised Partial Sentence Matching for Cited Text Identification. SDP@COLING Kathryn Ricci, Haw-Shiuan Chang, Purujit Goyal, Andrew McCallum
2022	—	`conf`	Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings. ACL (1) Shib Sankar Dasgupta, Michael Boratko, Siddhartha Mishra, Shriya Atmakuri, Dhruvesh Patel, Xiang Li, Andrew McCallum
2022	—	`conf`	You can't pick your neighbors, or can you? When and How to Rely on Retrieval in the kNN-LM. EMNLP (Findings) Andrew Drozdov, Shufan Wang, Razieh Rahimi, Andrew McCallum, Hamed Zamani, Mohit Iyyer
2022	J	`jnl`	You can't pick your neighbors, or can you? When and how to rely on retrieval in the kNN-LM. CoRR Andrew Drozdov, Shufan Wang, Razieh Rahimi, Andrew McCallum, Hamed Zamani, Mohit Iyyer
2021	—	`ed.`	3rd Conference on Automated Knowledge Base Construction, AKBC 2021, Virtual, October 4-8, 2021. AKBC Danqi Chen, Jonathan Berant, Andrew McCallum, Sameer Singh
2021	J	`jnl`	A Dataset for Discourse Structure in Peer Review Discussions. CoRR Neha Nayak Kennard, Tim O'Gorman, Akshay Sharma, Chhandak Bagchi, Matthew Clinton, Pranay Kumar Yelugam, Rajarshi Das, Hamed Zamani, Andrew McCallum
2021	—	`conf`	Benchmarking Scalable Methods for Streaming Cross Document Entity Coreference. ACL/IJCNLP (1) Robert L. Logan IV, Andrew McCallum, Sameer Singh, Daniel M. Bikel
2021	—	`conf`	Box Embeddings: An open-source library for representation learning using geometric structures. EMNLP (Demos) Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum
2021	J	`jnl`	Box Embeddings: An open-source library for representation learning using geometric structures. CoRR Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum
2021	—	`conf`	Box-To-Box Transformations for Modeling Joint Hierarchies. RepL4NLP@ACL-IJCNLP Shib Sankar Dasgupta, Xiang Lorraine Li, Michael Boratko, Dongxu Zhang, Andrew McCallum
2021	—	`conf`	CSFCube - A Test Collection of Computer Science Research Articles for Faceted Query by Example. NeurIPS Datasets and Benchmarks Sheshera Mysore, Tim O'Gorman, Andrew McCallum, Hamed Zamani
2021	J	`jnl`	CSFCube - A Test Collection of Computer Science Research Articles for Faceted Query by Example. CoRR Sheshera Mysore, Tim O'Gorman, Andrew McCallum, Hamed Zamani
2021	A*	`conf`	Capacity and Bias of Learned Geometric Embeddings for Directed Graphs. NeurIPS Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L. Clarkson, Andrew McCallum
2021	—	`conf`	Case-based Reasoning for Natural Language Queries over Knowledge Bases. EMNLP (1) Rajarshi Das, Manzil Zaheer, Dung Thai, Ameya Godbole, Ethan Perez, Jay Yoon Lee, Lizhen Tan, Lazaros Polymenakos, Andrew McCallum
2021	J	`jnl`	Case-based Reasoning for Natural Language Queries over Knowledge Bases. CoRR Rajarshi Das, Manzil Zaheer, Dung Thai, Ameya Godbole, Ethan Perez, Jay-Yoon Lee, Lizhen Tan, Lazaros Polymenakos, Andrew McCallum
2021	A	`conf`	Changing the Mind of Transformers for Topically-Controllable Language Generation. EACL Haw-Shiuan Chang, Jiaming Yuan, Mohit Iyyer, Andrew McCallum
2021	J	`jnl`	Changing the Mind of Transformers for Topically-Controllable Language Generation. CoRR Haw-Shiuan Chang, Jiaming Yuan, Mohit Iyyer, Andrew McCallum
2021	A	`conf`	Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering. AISTATS Sebastian Macaluso, Craig S. Greenberg, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum
2021	—	`conf`	Clustering-based Inference for Biomedical Entity Linking. NAACL-HLT Rico Angell, Nicholas Monath, Sunil Mohan, Nishant Yadav, Andrew McCallum
2021	A	`conf`	DAG-Structured Clustering by Nearest Neighbors. AISTATS Nicholas Monath, Manzil Zaheer, Kumar Avinava Dubey, Amr Ahmed, Andrew McCallum
2021	—	`conf`	Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP. EMNLP (1) Trapit Bansal, Karthick Prasad Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum
2021	J	`jnl`	Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP. CoRR Trapit Bansal, Karthick Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, Andrew McCallum
2021	—	`conf`	Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models. ACL/IJCNLP (1) Sumanta Bhattacharyya, Amirmohammad Rooshenas, Subhajit Naskar, Simeng Sun, Mohit Iyyer, Andrew McCallum
2021	J	`jnl`	Entity Linking and Discovery via Arborescence-based Supervised Clustering. CoRR Dhruv Agarwal, Rico Angell, Nicholas Monath, Andrew McCallum
2021	J	`jnl`	Exact and Approximate Hierarchical Clustering Using A. CoRR Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum
2021	A	`conf`	Exact and approximate hierarchical clustering using A. UAI Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum
2021	A*	`conf`	Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications. AAAI Haw-Shiuan Chang, Amol Agrawal, Andrew McCallum
2021	J	`jnl`	Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications. CoRR Haw-Shiuan Chang, Amol Agrawal, Andrew McCallum
2021	—	`conf`	Improved Latent Tree Induction with Distant Supervision via Span Constraints. EMNLP (1) Zhiyang Xu, Andrew Drozdov, Jay-Yoon Lee, Tim O'Gorman, Subendhu Rongali, Dylan Finkbeiner, Shilpa Suresh, Mohit Iyyer, Andrew McCallum
2021	J	`jnl`	Improved Latent Tree Induction with Distant Supervision via Span Constraints. CoRR Zhiyang Xu, Andrew Drozdov, Jay-Yoon Lee, Tim O'Gorman, Subendhu Rongali, Dylan Finkbeiner, Shilpa Suresh, Mohit Iyyer, Andrew McCallum
2021	—	`conf`	Knowledge Informed Semantic Parsing for Conversational Question Answering. RepL4NLP@ACL-IJCNLP Raghuveer Thirukovalluru, Mukund Sridhar, Dung Thai, Shruti Chanumolu, Nicholas Monath, Sankaranarayanan Ananthakrishnan, Andrew McCallum
2021	—	`conf`	Long Document Summarization in a Low Resource Setting using Pretrained Language Models. ACL (student) Ahsaas Bajaj, Pavitra Dangati, Kalpesh Krishna, Pradhiksha Ashok Kumar, Rheeya Uppaal, Bradford Windsor, Eliot Brenner, Dominic Dotterrer, Rajarshi Das, Andrew McCallum
2021	J	`jnl`	Long Document Summarization in a Low Resource Setting using Pretrained Language Models. CoRR Ahsaas Bajaj, Pavitra Dangati, Kalpesh Krishna, Pradhiksha Ashok Kumar, Rheeya Uppaal, Bradford Windsor, Eliot Brenner, Dominic Dotterrer, Rajarshi Das, Andrew McCallum
2021	J	`jnl`	Low Resource Recognition and Linking of Biomedical Concepts from a Large Ontology. CoRR Sunil Mohan, Rico Angell, Nicholas Monath, Andrew McCallum
2021	—	`conf`	Low resource recognition and linking of biomedical concepts from a large ontology. BCB Sunil Mohan, Rico Angell, Nicholas Monath, Andrew McCallum
2021	—	`conf`	MOLEMAN: Mention-Only Linking of Entities with a Mention Annotation Network. ACL/IJCNLP (2) Nicholas FitzGerald, Daniel M. Bikel, Jan A. Botha, Daniel Gillick, Tom Kwiatkowski, Andrew McCallum
2021	J	`jnl`	MOLEMAN: Mention-Only Linking of Entities with a Mention Annotation Network. CoRR Nicholas FitzGerald, Jan A. Botha, Daniel Gillick, Daniel M. Bikel, Tom Kwiatkowski, Andrew McCallum
2021	—	`conf`	MS-Mentions: Consistently Annotating Entity Mentions in Materials Science Procedural Text. EMNLP (1) Tim O'Gorman, Zach Jensen, Sheshera Mysore, Kevin Huang, Rubayyat Mahbub, Elsa A. Olivetti, Andrew McCallum
2021	A	`conf`	Min/max stability and box distributions. UAI Michael Boratko, Javier Burroni, Shib Sankar Dasgupta, Andrew McCallum
2021	—	`conf`	Modeling Fine-Grained Entity Types with Box Embeddings. ACL/IJCNLP (1) Yasumasa Onoe, Michael Boratko, Andrew McCallum, Greg Durrett
2021	A	`conf`	Multi-facet Universal Schema. EACL Rohan Paul, Haw-Shiuan Chang, Andrew McCallum
2021	J	`jnl`	Multi-facet Universal Schema. CoRR Rohan Paul, Haw-Shiuan Chang, Andrew McCallum
2021	—	`conf`	Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. NAACL-HLT Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum
2021	J	`jnl`	Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning. CoRR Xuelu Chen, Michael Boratko, Muhao Chen, Shib Sankar Dasgupta, Xiang Lorraine Li, Andrew McCallum
2021	A*	`conf`	Scalable Hierarchical Agglomerative Clustering. KDD Nicholas Monath, Kumar Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu
2021	—	`conf`	Scaling Within Document Coreference to Long Texts. ACL/IJCNLP (Findings) Raghuveer Thirukovalluru, Nicholas Monath, Kumar Shridhar, Manzil Zaheer, Mrinmaya Sachan, Andrew McCallum
2021	—	`conf`	Simultaneously Self-Attending to Text and Entities for Knowledge-Informed Text Representations. RepL4NLP@ACL-IJCNLP Dung Thai, Raghuveer Thirukovalluru, Trapit Bansal, Andrew McCallum
2021	J	`jnl`	Sublinear Time Approximation of Text Similarity Matrices. CoRR Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco
2021	J	`jnl`	Word2Box: Learning Word Representation Using Box Embeddings. CoRR Shib Sankar Dasgupta, Michael Boratko, Shriya Atmakuri, Xiang Lorraine Li, Dhruvesh Patel, Andrew McCallum
2020	—	`conf`	A Simple Approach to Case-Based Reasoning in Knowledge Bases. AKBC Rajarshi Das, Ameya Godbole, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum
2020	J	`jnl`	A Simple Approach to Case-Based Reasoning in Knowledge Bases. CoRR Rajarshi Das, Ameya Godbole, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum
2020	—	`conf`	An Instance Level Approach for Shallow Semantic Parsing in Scientific Procedural Text. EMNLP (Findings) Daivik Swarup, Ahsaas Bajaj, Sheshera Mysore, Tim O'Gorman, Rajarshi Das, Andrew McCallum
2020	A*	`conf`	AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types. KDD Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, Jiawei Han
2020	J	`jnl`	AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types. CoRR Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, Jiawei Han
2020	J	`jnl`	Clustering-based Inference for Zero-Shot Biomedical Entity Linking. CoRR Rico Angell, Nicholas Monath, Sunil Mohan, Nishant Yadav, Andrew McCallum
2020	J	`jnl`	Compact Representation of Uncertainty in Hierarchical Clustering. CoRR Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum
2020	—	`ed.`	Conference on Automated Knowledge Base Construction, AKBC 2020, Virtual, June 22-24, 2020. AKBC Dipanjan Das, Hannaneh Hajishirzi, Andrew McCallum, Sameer Singh
2020	A*	`conf`	Energy and Policy Considerations for Modern Deep Learning Research. AAAI Emma Strubell, Ananya Ganesh, Andrew McCallum
2020	J	`jnl`	Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models. CoRR Subhajit Naskar, Amirmohammad Rooshenas, Simeng Sun, Mohit Iyyer, Andrew McCallum
2020	A*	`conf`	Improving Local Identifiability in Probabilistic Box Embeddings. NeurIPS Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Li, Andrew McCallum
2020	J	`jnl`	Improving Local Identifiability in Probabilistic Box Embeddings. CoRR Shib Sankar Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Lorraine Li, Andrew McCallum
2020	J	`jnl`	Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks. J. Chem. Inf. Model. Edward Kim, Zach Jensen, Alexander van Grootel, Kevin Huang, Matthew Staib, Sheshera Mysore, Haw-Shiuan Chang, Emma Strubell, Andrew McCallum, Stefanie Jegelka, Elsa A. Olivetti
2020	B	`conf`	Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks. COLING Trapit Bansal, Rishikesh Jha, Andrew McCallum
2020	—	`conf`	Predicting Institution Hierarchies with Set-based Models. AKBC Derek Tam, Nicholas Monath, Ari Kobren, Andrew McCallum
2020	J	`jnl`	Probabilistic Case-based Reasoning for Open-World Knowledge Graph Completion. CoRR Rajarshi Das, Ameya Godbole, Nicholas Monath, Manzil Zaheer, Andrew McCallum
2020	—	`conf`	Probabilistic Case-based Reasoning in Knowledge Bases. EMNLP (Findings) Rajarshi Das, Ameya Godbole, Nicholas Monath, Manzil Zaheer, Andrew McCallum
2020	—	`conf`	ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning. EMNLP (1) Michael Boratko, Xiang Li, Tim O'Gorman, Rajarshi Das, Dan Le, Andrew McCallum
2020	J	`jnl`	ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning. CoRR Michael Boratko, Xiang Lorraine Li, Rajarshi Das, Tim O'Gorman, Dan Le, Andrew McCallum
2020	—	`conf`	Representing Joint Hierarchies with Box Embeddings. AKBC Dhruvesh Patel, Shib Sankar Dasgupta, Michael Boratko, Xiang Li, Luke Vilnis, Andrew McCallum
2020	J	`jnl`	Scalable Bottom-Up Hierarchical Clustering. CoRR Nicholas Monath, Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gökhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu
2020	J	`jnl`	Scalable Hierarchical Clustering with Tree Grafting. CoRR Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael R. Glass, Andrew McCallum
2020	—	`conf`	Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks. EMNLP (1) Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum
2020	J	`jnl`	Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks. CoRR Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum
2020	A*	`conf`	Simultaneously Linking Entities and Extracting Relations from Biomedical Text without Mention-Level Supervision. AAAI Trapit Bansal, Patrick Verga, Neha Choudhary, Andrew McCallum
2020	—	`conf`	Unsupervised Parsing with S-DIORA: Single Tree Encoding for Deep Inside-Outside Recursive Autoencoders. EMNLP (1) Andrew Drozdov, Subendhu Rongali, Yi-Pei Chen, Tim O'Gorman, Mohit Iyyer, Andrew McCallum
2020	—	`conf`	Unsupervised Pre-training for Biomedical Question Answering. CLEF (Working Notes) Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li, Trapit Bansal, Andrew McCallum, Ivana Williams, Ana-Maria Istrate
2020	J	`jnl`	Unsupervised Pre-training for Biomedical Question Answering. CoRR Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li, Trapit Bansal, Andrew McCallum, Ivana Williams, Ana-Maria Istrate
2020	—	`conf`	Using BibTeX to Automatically Generate Labeled Data for Citation Field Extraction. AKBC Dung Thai, Zhiyang Xu, Nicholas Monath, Boris Veytsman, Andrew McCallum
2020	J	`jnl`	Using BibTeX to Automatically Generate Labeled Data for Citation Field Extraction. CoRR Dung Thai, Zhiyang Xu, Nicholas Monath, Boris Veytsman, Andrew McCallum
2020	J	`jnl`	Using error decay prediction to overcome practical issues of deep active learning for named entity recognition. Mach. Learn. Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, Andrew McCallum
2019	—	`conf`	A2N: Attending to Neighbors for Knowledge Graph Inference. ACL (1) Trapit Bansal, Da-Cheng Juan, Sujith Ravi, Andrew McCallum
2019	—	`conf`	Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension. ICLR (Poster) Rajarshi Das, Tsendsuren Munkhdalai, Xingdi Yuan, Adam Trischler, Andrew McCallum
2019	—	`conf`	Chains-of-Reasoning at TextGraphs 2019 Shared Task: Reasoning over Chains of Facts for Explainable Multi-hop Inference. TextGraphs@EMNLP Rajarshi Das, Ameya Godbole, Manzil Zaheer, Shehzaad Dhuliawala, Andrew McCallum
2019	—	`conf`	Energy and Policy Considerations for Deep Learning in NLP. ACL (1) Emma Strubell, Ananya Ganesh, Andrew McCallum
2019	J	`jnl`	Energy and Policy Considerations for Deep Learning in NLP. CoRR Emma Strubell, Ananya Ganesh, Andrew McCallum
2019	A*	`conf`	Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. KDD Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed
2019	J	`jnl`	Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks. CoRR Edward Kim, Zach Jensen, Alexander van Grootel, Kevin Huang, Matthew Staib, Sheshera Mysore, Haw-Shiuan Chang, Emma Strubell, Andrew McCallum, Stefanie Jegelka, Elsa A. Olivetti
2019	—	`conf`	Integrating User Feedback under Identity Uncertainty in Knowledge Base Construction. AKBC Ari Kobren, Nicholas Monath, Andrew McCallum
2019	J	`jnl`	Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks. CoRR Trapit Bansal, Rishikesh Jha, Andrew McCallum
2019	—	`conf`	Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering. MRQA@EMNLP Rajarshi Das, Ameya Godbole, Dilip Kavarthapu, Zhiyu Gong, Abhishek Singhal, Mo Yu, Xiaoxiao Guo, Tian Gao, Hamed Zamani, Manzil Zaheer, Andrew McCallum
2019	J	`jnl`	Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering. CoRR Ameya Godbole, Dilip Kavarthapu, Rajarshi Das, Zhiyu Gong, Abhishek Singhal, Hamed Zamani, Mo Yu, Tian Gao, Xiaoxiao Guo, Manzil Zaheer, Andrew McCallum
2019	—	`conf`	Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering. ICLR (Poster) Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum
2019	J	`jnl`	Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering. CoRR Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Andrew McCallum
2019	—	`conf`	OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference. NAACL-HLT (1) Dongxu Zhang, Subhabrata Mukherjee, Colin Lockard, Xin Luna Dong, Andrew McCallum
2019	J	`jnl`	OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference. CoRR Dongxu Zhang, Subhabrata Mukherjee, Colin Lockard, Xin Luna Dong, Andrew McCallum
2019	—	`conf`	Optimal Transport-based Alignment of Learned Character Representations for String Similarity. ACL (1) Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor, Rajarshi Das, Andrew McCallum
2019	J	`jnl`	Optimal Transport-based Alignment of Learned Character Representations for String Similarity. CoRR Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor, Rajarshi Das, Andrew McCallum
2019	J	`jnl`	Overcoming Practical Issues of Deep Active Learning and its Applications on Named Entity Recognition. CoRR Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, Andrew McCallum
2019	A*	`conf`	Paper Matching with Local Fairness Constraints. KDD Ari Kobren, Barna Saha, Andrew McCallum
2019	J	`jnl`	Paper Matching with Local Fairness Constraints. CoRR Ari Kobren, Barna Saha, Andrew McCallum
2019	B	`conf`	Roll Call Vote Prediction with Knowledge Augmented Models. CoNLL Pallavi Patil, Kriti Myer, Ronak Zala, Arpit Singh, Sheshera Mysore, Andrew McCallum, Adrian Benton, Amanda Stent
2019	A*	`conf`	Scalable Hierarchical Clustering with Tree Grafting. KDD Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael R. Glass, Andrew McCallum
2019	A*	`conf`	Search-Guided, Lightly-Supervised Training of Structured Prediction Energy Networks. NeurIPS Amirmohammad Rooshenas, Dongxu Zhang, Gopal Sharma, Andrew McCallum
2019	J	`jnl`	Simultaneously Linking Entities and Extracting Relations from Biomedical Text Without Mention-level Supervision. CoRR Trapit Bansal, Patrick Verga, Neha Choudhary, Andrew McCallum
2019	—	`conf`	Smoothing the Geometry of Probabilistic Box Embeddings. ICLR Xiang Li, Luke Vilnis, Dongxu Zhang, Michael Boratko, Andrew McCallum
2019	A*	`conf`	Supervised Hierarchical Clustering with Exponential Linkage. ICML Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum
2019	J	`jnl`	Supervised Hierarchical Clustering with Exponential Linkage. CoRR Nishant Yadav, Ari Kobren, Nicholas Monath, Andrew McCallum
2019	—	`conf`	The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures. LAW@ACL Sheshera Mysore, Zach Jensen, Edward Kim, Kevin Huang, Haw-Shiuan Chang, Emma Strubell, Jeffrey Flanigan, Andrew McCallum, Elsa A. Olivetti
2019	J	`jnl`	The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures. CoRR Sheshera Mysore, Zach Jensen, Edward Kim, Kevin Huang, Haw-Shiuan Chang, Emma Strubell, Jeffrey Flanigan, Andrew McCallum, Elsa A. Olivetti
2019	—	`conf`	Unsupervised Labeled Parsing with Deep Inside-Outside Recursive Autoencoders. EMNLP/IJCNLP (1) Andrew Drozdov, Patrick Verga, Yi-Pei Chen, Mohit Iyyer, Andrew McCallum
2019	—	`conf`	Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Auto-Encoders. NAACL-HLT (1) Andrew Drozdov, Patrick Verga, Mohit Yadav, Mohit Iyyer, Andrew McCallum
2019	J	`jnl`	Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Autoencoders. CoRR Andrew Drozdov, Patrick Verga, Mohit Yadav, Mohit Iyyer, Andrew McCallum
2018	—	`conf`	A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset. QA@ACL Michael Boratko, Harshit Padigela, Divyendra Mikkilineni, Pritish Yuvraj, Rajarshi Das, Andrew McCallum, Maria Chang, Achille Fokoue-Nkoutche, Pavan Kapanipathi, Nicholas Mattei, Ryan Musa, Kartik Talamadupula, Michael Witbrock
2018	J	`jnl`	A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset. CoRR Michael Boratko, Harshit Padigela, Divyendra Mikkilineni, Pritish Yuvraj, Rajarshi Das, Andrew McCallum, Maria Chang, Achille Fokoue-Nkoutche, Pavan Kapanipathi, Nicholas Mattei, Ryan Musa, Kartik Talamadupula, Michael Witbrock
2018	—	`conf`	An Interface for Annotating Science Questions. EMNLP (Demonstration) Michael Boratko, Harshit Padigela, Divyendra Mikkilineni, Pritish Yuvraj, Rajarshi Das, Andrew McCallum, Maria Chang, Achille Fokoue, Pavan Kapanipathi, Nicholas Mattei, Ryan Musa, Kartik Talamadupula, Michael Witbrock
2018	J	`jnl`	Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension. CoRR Rajarshi Das, Tsendsuren Munkhdalai, Xingdi Yuan, Adam Trischler, Andrew McCallum
2018	A*	`conf`	Compact Representation of Uncertainty in Clustering. NeurIPS Craig S. Greenberg, Nicholas Monath, Ari Kobren, Patrick Flaherty, Andrew McGregor, Andrew McCallum
2018	—	`conf`	Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection. NAACL-HLT Haw-Shiuan Chang, Ziyun Wang, Luke Vilnis, Andrew McCallum
2018	—	`conf`	Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings. TextGraphs@NAACL-HLT Haw-Shiuan Chang, Amol Agrawal, Ananya Ganesh, Anirudha Desai, Vinayak Mathur, Alfred Hough, Andrew McCallum
2018	J	`jnl`	Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings. CoRR Haw-Shiuan Chang, Amol Agrawal, Ananya Ganesh, Anirudha Desai, Vinayak Mathur, Alfred Hough, Andrew McCallum
2018	B	`conf`	Embedded-State Latent Conditional Random Fields for Sequence Labeling. CoNLL Dung Thai, Sree Harsha Ramesh, Shikhar Murty, Luke Vilnis, Andrew McCallum
2018	J	`jnl`	Embedded-State Latent Conditional Random Fields for Sequence Labeling. CoRR Dung Thai, Sree Harsha Ramesh, Shikhar Murty, Luke Vilnis, Andrew McCallum
2018	—	`conf`	Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning. ICLR (Poster) Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum
2018	—	`conf`	Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking. ACL (1) Shikhar Murty, Patrick Verga, Luke Vilnis, Irena Radovanovic, Andrew McCallum
2018	J	`jnl`	Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking. CoRR Shikhar Murty, Patrick Verga, Luke Vilnis, Irena Radovanovic, Andrew McCallum
2018	A*	`conf`	Linguistically-Informed Self-Attention for Semantic Role Labeling. EMNLP Emma Strubell, Patrick Verga, Daniel Andor, David Weiss, Andrew McCallum
2018	J	`jnl`	Linguistically-Informed Self-Attention for Semantic Role Labeling. CoRR Emma Strubell, Patrick Verga, Daniel Andor, David Weiss, Andrew McCallum
2018	A*	`conf`	Marginal Likelihood Training of BiLSTM-CRF for Biomedical Named Entity Recognition from Disjoint Label Sets. EMNLP Nathan Greenberg, Trapit Bansal, Patrick Verga, Andrew McCallum
2018	—	`conf`	Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures. ACL (1) Luke Vilnis, Xiang Li, Shikhar Murty, Andrew McCallum
2018	J	`jnl`	Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures. CoRR Luke Vilnis, Xiang Li, Shikhar Murty, Andrew McCallum
2018	J	`jnl`	Search-Guided, Lightly-supervised Training of Structured Prediction Energy Networks. CoRR Amirmohammad Rooshenas, Dongxu Zhang, Gopal Sharma, Andrew McCallum
2018	—	`conf`	Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction. NAACL-HLT Patrick Verga, Emma Strubell, Andrew McCallum
2018	J	`jnl`	Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction. CoRR Patrick Verga, Emma Strubell, Andrew McCallum
2018	J	`jnl`	Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL? CoRR Emma Strubell, Andrew McCallum
2018	—	`conf`	Training Structured Prediction Energy Networks with Indirect Supervision. NAACL-HLT (2) Amirmohammad Rooshenas, Aishwarya Kamath, Andrew McCallum
2017	A*	`conf`	A Hierarchical Algorithm for Extreme Clustering. KDD Ari Kobren, Nicholas Monath, Akshay Krishnamurthy, Andrew McCallum
2017	—	`conf`	Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples. NIPS Haw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum
2017	J	`jnl`	Active Bias: Training a More Accurate Neural Network by Emphasizing High Variance Samples. CoRR Haw-Shiuan Chang, Erik G. Learned-Miller, Andrew McCallum
2017	J	`jnl`	An Online Hierarchical Algorithm for Extreme Clustering. CoRR Ari Kobren, Nicholas Monath, Akshay Krishnamurthy, Andrew McCallum
2017	—	`conf`	Attending to All Mention Pairs for Full Abstract Biological Relation Extraction. AKBC@NIPS Patrick Verga, Emma Strubell, Ofer Shai, Andrew McCallum
2017	J	`jnl`	Attending to All Mention Pairs for Full Abstract Biological Relation Extraction. CoRR Patrick Verga, Emma Strubell, Ofer Shai, Andrew McCallum
2017	J	`jnl`	Automatically Extracting Action Graphs from Materials Science Synthesis Procedures. CoRR Sheshera Mysore, Edward Kim, Emma Strubell, Ao Liu, Haw-Shiuan Chang, Srikrishna Kompella, Kevin Huang, Andrew McCallum, Elsa A. Olivetti
2017	—	`conf`	Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. EACL (1) Rajarshi Das, Arvind Neelakantan, David Belanger, Andrew McCallum
2017	—	`conf`	Dependency Parsing with Dilated Iterated Graph CNNs. SPNLP@EMNLP Emma Strubell, Andrew McCallum
2017	J	`jnl`	Dependency Parsing with Dilated Iterated Graph CNNs. CoRR Emma Strubell, Andrew McCallum
2017	A*	`conf`	End-to-End Learning for Structured Prediction Energy Networks. ICML David Belanger, Bishan Yang, Andrew McCallum
2017	J	`jnl`	End-to-End Learning for Structured Prediction Energy Networks. CoRR David Belanger, Bishan Yang, Andrew McCallum
2017	—	`conf`	Entity-centric Attribute Feedback for Interactive Knowledge Bases. AKBC@NIPS Ari Kobren, Nicholas Monath, Andrew McCallum
2017	A*	`conf`	Fast and Accurate Entity Recognition with Iterated Dilated Convolutions. EMNLP Emma Strubell, Patrick Verga, David Belanger, Andrew McCallum
2017	J	`jnl`	Fast and Accurate Sequence Labeling with Iterated Dilated Convolutions. CoRR Emma Strubell, Patrick Verga, David Belanger, Andrew McCallum
2017	—	`conf`	Finer Grained Entity Typing with TypeNet. AKBC@NIPS Shikhar Murty, Patrick Verga, Luke Vilnis, Andrew McCallum
2017	J	`jnl`	Finer Grained Entity Typing with TypeNet. CoRR Shikhar Murty, Patrick Verga, Luke Vilnis, Andrew McCallum
2017	—	`conf`	Generalizing to Unseen Entities and Entity Pairs with Row-less Universal Schema. EACL (1) Patrick Verga, Arvind Neelakantan, Andrew McCallum
2017	—	`conf`	Go for a Walk and Arrive at the Answer: Reasoning Over Knowledge Bases with Reinforcement Learning. AKBC@NIPS Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum
2017	J	`jnl`	Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning. CoRR Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alexander J. Smola, Andrew McCallum
2017	J	`jnl`	Improved Representation Learning for Predicting Commonsense Ontologies. CoRR Xiang Li, Luke Vilnis, Andrew McCallum
2017	—	`conf`	Learning String Alignments for Entity Aliases. AKBC@NIPS Aaron Traylor, Nicholas Monath, Rajarshi Das, Andrew McCallum
2017	—	`conf`	Learning a Natural Language Interface with Neural Programmer. ICLR (Poster) Arvind Neelakantan, Quoc V. Le, Martín Abadi, Andrew McCallum, Dario Amodei
2017	J	`jnl`	Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling. CoRR Dung Thai, Shikhar Murty, Trapit Bansal, Luke Vilnis, David Belanger, Andrew McCallum
2017	—	`conf`	Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks. ACL (2) Rajarshi Das, Manzil Zaheer, Siva Reddy, Andrew McCallum
2017	J	`jnl`	Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks. CoRR Rajarshi Das, Manzil Zaheer, Siva Reddy, Andrew McCallum
2017	—	`conf`	RelNet: End-to-end Modeling of Entities & Relations. AKBC@NIPS Trapit Bansal, Arvind Neelakantan, Andrew McCallum
2017	J	`jnl`	RelNet: End-to-end Modeling of Entities & Relations. CoRR Trapit Bansal, Arvind Neelakantan, Andrew McCallum
2017	—	`conf`	SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications. SemEval@ACL Isabelle Augenstein, Mrinal Das, Sebastian Riedel, Lakshmi Vikraman, Andrew McCallum
2017	J	`jnl`	SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications. CoRR Isabelle Augenstein, Mrinal Das, Sebastian Riedel, Lakshmi Vikraman, Andrew McCallum
2017	J	`jnl`	Unsupervised Hypernym Detection by Distributional Inclusion Vector Embedding. CoRR Haw-Shiuan Chang, Ziyun Wang, Luke Vilnis, Andrew McCallum
2016	J	`jnl`	Ask the GRU: Multi-Task Learning for Deep Text Recommendations. CoRR Trapit Bansal, David Belanger, Andrew McCallum
2016	—	`conf`	Call for Discussion: Building a New Standard Dataset for Relation Extraction Tasks. AKBC@NAACL-HLT Teresa Martin, Fiete Botschen, Ajay Nagesh, Andrew McCallum
2016	J	`jnl`	Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. CoRR Rajarshi Das, Arvind Neelakantan, David Belanger, Andrew McCallum
2016	—	`conf`	Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema. TAC Haw-Shiuan Chang, Abdurrahman Munir, Ao Liu, Johnny Tian-Zheng Wei, Aaron Traylor, Ajay Nagesh, Nicholas Monath, Patrick Verga, Emma Strubell, Andrew McCallum
2016	J	`jnl`	Generalizing to Unseen Entities and Entity Pairs with Row-less Universal Schema. CoRR Patrick Verga, Arvind Neelakantan, Andrew McCallum
2016	—	`conf`	Incorporating Selectional Preferences in Multi-hop Relation Extraction. AKBC@NAACL-HLT Rajarshi Das, Arvind Neelakantan, David Belanger, Andrew McCallum
2016	J	`jnl`	Learning a Natural Language Interface with Neural Programmer. CoRR Arvind Neelakantan, Quoc V. Le, Martín Abadi, Andrew McCallum, Dario Amodei
2016	—	`conf`	Multilingual Relation Extraction using Compositional Universal Schema. HLT-NAACL Patrick Verga, David Belanger, Emma Strubell, Benjamin Roth, Andrew McCallum
2016	—	`conf`	Row-less Universal Schema. AKBC@NAACL-HLT Patrick Verga, Andrew McCallum
2016	J	`jnl`	Row-less Universal Schema. CoRR Patrick Verga, Andrew McCallum
2016	A*	`conf`	Structured Prediction Energy Networks. ICML David Belanger, Andrew McCallum
2015	A	`conf`	Bethe Projections for Non-Local Inference. UAI Luke Vilnis, David Belanger, Daniel Sheldon, Andrew McCallum
2015	J	`jnl`	Bethe Projections for Non-Local Inference. CoRR Luke Vilnis, David Belanger, Daniel Sheldon, Andrew McCallum
2015	—	`conf`	Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches. TAC Benjamin Roth, Nicholas Monath, David Belanger, Emma Strubell, Patrick Verga, Andrew McCallum
2015	—	`conf`	Compositional Vector Space Models for Knowledge Base Completion. ACL (1) Arvind Neelakantan, Benjamin Roth, Andrew McCallum
2015	J	`jnl`	Compositional Vector Space Models for Knowledge Base Completion. CoRR Arvind Neelakantan, Benjamin Roth, Andrew McCallum
2015	—	`conf`	Compositional Vector Space Models for Knowledge Base Inference. AAAI Spring Symposia Arvind Neelakantan, Benjamin Roth, Andrew McCallum
2015	J	`jnl`	Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space. CoRR Arvind Neelakantan, Jeevan Shankar, Alexandre Passos, Andrew McCallum
2015	Misc	`conf`	Embedded Representations of Lexical and Knowledge-Base Semantics. ICTIR Andrew McCallum
2015	—	`conf`	Learning Dynamic Feature Selection for Fast Sequential Prediction. ACL (1) Emma Strubell, Luke Vilnis, Kate Silverstein, Andrew McCallum
2015	J	`jnl`	Learning Dynamic Feature Selection for Fast Sequential Prediction. CoRR Emma Strubell, Luke Vilnis, Kate Silverstein, Andrew McCallum
2015	J	`jnl`	Multilingual Relation Extraction using Compositional Universal Schema. CoRR Patrick Verga, David Belanger, Emma Strubell, Benjamin Roth, Andrew McCallum
2015	J	`jnl`	Reports on the 2015 AAAI Spring Symposium Series. AI Mag. Nitin Agarwal, Sean Andrist, Dan Bohus, Fei Fang, Laurie Fenstermacher, Lalana Kagal, Takashi Kido, Christopher Kiekintveld, William F. Lawless, Huan Liu, Andrew McCallum, Hemant Purohit, Oshani Seneviratne, Keiki Takadama, Gavin Taylor
2015	J	`jnl`	Structured Prediction Energy Networks. CoRR David Belanger, Andrew McCallum
2015	—	`conf`	Word Representations via Gaussian Embedding. ICLR Luke Vilnis, Andrew McCallum
2014	A*	`conf`	Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space. EMNLP Arvind Neelakantan, Jeevan Shankar, Alexandre Passos, Andrew McCallum
2014	—	`conf`	Learning Soft Linear Constraints with Application to Citation Field Extraction. ACL (1) Sam Anzaroot, Alexandre Passos, David Belanger, Andrew McCallum
2014	J	`jnl`	Learning Soft Linear Constraints with Application to Citation Field Extraction. CoRR Sam Anzaroot, Alexandre Passos, David Belanger, Andrew McCallum
2014	B	`conf`	Lexicon Infused Phrase Embeddings for Named Entity Resolution. CoNLL Alexandre Passos, Vineet Kumar, Andrew McCallum
2014	J	`jnl`	Lexicon Infused Phrase Embeddings for Named Entity Resolution. CoRR Alexandre Passos, Vineet Kumar, Andrew McCallum
2014	A	`conf`	Message Passing for Soft Constraint Dual Decomposition. UAI David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum
2014	J	`jnl`	Training for Fast Sequential Prediction Using Dynamic Feature Selection. CoRR Emma Strubell, Luke Vilnis, Andrew McCallum
2013	—	`conf`	A joint model for discovering and linking entities. AKBC@CIKM Michael L. Wick, Sameer Singh, Harshal Pandya, Andrew McCallum
2013	J	`jnl`	Anytime Belief Propagation Using Sparse Domains. CoRR Sameer Singh, Sebastian Riedel, Andrew McCallum
2013	—	`conf`	Assessing confidence of knowledge base content with an experimental study in entity resolution. AKBC@CIKM Michael L. Wick, Sameer Singh, Ari Kobren, Andrew McCallum
2013	B	`conf`	Dynamic Knowledge-Base Alignment for Coreference Resolution. CoNLL Jiaping Zheng, Luke Vilnis, Sameer Singh, Jinho D. Choi, Andrew McCallum
2013	—	`conf`	Joint inference of entities, relations, and coreference. AKBC@CIKM Sameer Singh, Sebastian Riedel, Brian Martin, Jiaping Zheng, Andrew McCallum
2013	—	`conf`	Latent Relation Representations for Universal Schemas ICLR (Workshop Poster) Sebastian Riedel, Limin Yao, Andrew McCallum
2013	J	`jnl`	Learning with Scope, with Application to Information Extraction and Classification CoRR David M. Blei, J. Andrew Bagnell, Andrew McCallum
2013	—	`conf`	Relation Extraction with Matrix Factorization and Universal Schemas. HLT-NAACL Sebastian Riedel, Limin Yao, Andrew McCallum, Benjamin M. Marlin
2013	—	`conf`	Transition-based Dependency Parsing with Selectional Branching. ACL (1) Jinho D. Choi, Andrew McCallum
2013	—	`conf`	Universal Schema for Slot Filling and Cold Start: UMass IESL at TACKBP 2013. TAC Sameer Singh, Limin Yao, David Belanger, Ari Kobren, Sam Anzaroot, Mike Wick, Alexandre Passos, Harshal Pandya, Jinho D. Choi, Brian Martin, Andrew McCallum
2013	—	`conf`	Universal schema for entity type prediction. AKBC@CIKM Limin Yao, Sebastian Riedel, Andrew McCallum
2012	J	`jnl`	A Conditional Random Field for Discriminatively-trained Finite-state String Edit Distance CoRR Andrew McCallum, Kedar Bellare, Fernando C. N. Pereira
2012	—	`conf`	A Discriminative Hierarchical Model for Fast Coreference at Large Scale. ACL (1) Michael L. Wick, Sameer Singh, Andrew McCallum
2012	J	`jnl`	Alternating Projections for Learning with Expectation Constraints CoRR Kedar Bellare, Gregory Druck, Andrew McCallum
2012	J	`jnl`	An Integrated, Conditional Model of Information Extraction and Coreference with Applications to Citation Matching CoRR Ben Wellner, Andrew McCallum, Fuchun Peng, Michael Hay
2012	J	`jnl`	An Introduction to Conditional Random Fields. Found. Trends Mach. Learn. Charles Sutton, Andrew McCallum
2012	J	`jnl`	Combining joint models for biomedical event extraction. BMC Bioinform. David McClosky, Sebastian Riedel, Mihai Surdeanu, Andrew McCallum, Christopher D. Manning
2012	J	`jnl`	Efficiently Inducing Features of Conditional Random Fields CoRR Andrew McCallum
2012	—	`conf`	Human-Machine Cooperation: Supporting User Corrections to Automatically Constructed KBs. AKBC-WEKEX@NAACL-HLT Michael L. Wick, Karl Schultz, Andrew McCallum
2012	J	`jnl`	Improved Dynamic Schedules for Belief Propagation CoRR Charles Sutton, Andrew McCallum
2012	J	`jnl`	Inference by Minimizing Size, Divergence, or their Sum CoRR Sebastian Riedel, David A. Smith, Andrew McCallum
2012	—	`conf`	MAP Inference in Chains using Column Generation. NIPS David Belanger, Alexandre Passos, Sebastian Riedel, Andrew McCallum
2012	—	`conf`	Monte Carlo MCMC: Efficient Inference by Approximate Sampling. EMNLP-CoNLL Sameer Singh, Michael L. Wick, Andrew McCallum
2012	—	`conf`	Monte Carlo MCMC: Efficient Inference by Sampling Factors. AKBC-WEKEX@NAACL-HLT Sameer Singh, Michael L. Wick, Andrew McCallum
2012	J	`jnl`	Nonparametric Bayes Pachinko Allocation CoRR Wei Li, David M. Blei, Andrew McCallum
2012	—	`conf`	Parse, Price and Cut--Delayed Column and Row Generation for Graph Based Parsers. EMNLP-CoNLL Sebastian Riedel, David A. Smith, Andrew McCallum
2012	J	`jnl`	Piecewise Training for Undirected Models CoRR Charles Sutton, Andrew McCallum
2012	—	`conf`	Probabilistic Databases of Universal Schema. AKBC-WEKEX@NAACL-HLT Limin Yao, Sebastian Riedel, Andrew McCallum
2012	A	`conf`	Selecting actions for resource-bounded information extraction using reinforcement learning. WSDM Pallika H. Kanani, Andrew McCallum
2012	J	`jnl`	Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression CoRR David M. Mimno, Andrew McCallum
2012	—	`conf`	Topic models for taxonomies. JCDL Anton Bakalov, Andrew McCallum, Hanna M. Wallach, David M. Mimno
2012	—	`conf`	Unsupervised Relation Discovery with Sense Disambiguation. ACL (1) Limin Yao, Sebastian Riedel, Andrew McCallum
2011	A*	`conf`	Fast and Robust Joint Models for Biomedical Event Extraction. EMNLP Sebastian Riedel, Andrew McCallum
2011	A*	`conf`	Large-Scale Cross-Document Coreference Using Distributed Inference and Hierarchical Models. ACL Sameer Singh, Amarnag Subramanya, Fernando C. N. Pereira, Andrew McCallum
2011	—	`conf`	Model Combination for Event Extraction in BioNLP 2011. BioNLP@ACL (Shared Task) Sebastian Riedel, David McClosky, Mihai Surdeanu, Andrew McCallum, Christopher D. Manning
2011	A*	`conf`	Optimizing Semantic Coherence in Topic Models. EMNLP David M. Mimno, Hanna M. Wallach, Edmund M. Talley, Miriam Leenders, Andrew McCallum
2011	—	`conf`	Query-Aware MCMC. NIPS Michael L. Wick, Andrew McCallum
2011	—	`conf`	Robust Biomedical Event Extraction with Dual Decomposition and Minimal Domain Adaptation. BioNLP@ACL (Shared Task) Sebastian Riedel, Andrew McCallum
2011	A*	`conf`	SampleRank: Training Factor Graphs with Atomic Gradients. ICML Michael L. Wick, Khashayar Rohanimanesh, Kedar Bellare, Aron Culotta, Andrew McCallum
2011	A*	`conf`	Structured Relation Discovery using Generative Models. EMNLP Limin Yao, Aria Haghighi, Sebastian Riedel, Andrew McCallum
2011	A	`conf`	Toward interactive training and evaluation. CIKM Gregory Druck, Andrew McCallum
2010	A*	`conf`	Collective Cross-Document Relation Extraction Without Labelled Data. EMNLP Limin Yao, Sebastian Riedel, Andrew McCallum
2010	—	`conf`	Constraint-Driven Rank-Based Learning for Information Extraction. HLT-NAACL Sameer Singh, Limin Yao, Sebastian Riedel, Andrew McCallum
2010	J	`jnl`	Distantly Labeling Data for Large Scale Cross-Document Coreference CoRR Sameer Singh, Michael L. Wick, Andrew McCallum
2010	J	`jnl`	Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data. J. Mach. Learn. Res. Gideon S. Mann, Andrew McCallum
2010	A*	`conf`	High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models. ICML Gregory Druck, Andrew McCallum
2010	A	`conf`	Inference by Minimizing Size, Divergence, or their Sum. UAI Sebastian Riedel, David A. Smith, Andrew McCallum
2010	Misc	`conf`	Machine Translation Using Overlapping Alignments and SampleRank. AMTA Benjamin Roth, Andrew McCallum, Marc Dymetman, Nicola Cancedda
2010	—	`conf`	Modeling Relations and Their Mentions without Labeled Text. ECML/PKDD (3) Sebastian Riedel, Limin Yao, Andrew McCallum
2010	—	`conf`	Resource-Bounded Information Extraction: Acquiring Missing Feature Values on Demand. PAKDD (1) Pallika H. Kanani, Andrew McCallum, Shaohan Hu
2010	J	`jnl`	Scalable Probabilistic Databases with Factor Graphs and MCMC CoRR Michael L. Wick, Andrew McCallum, Gerome Miklau
2010	J	`jnl`	Scalable Probabilistic Databases with Factor Graphs and MCMC. Proc. VLDB Endow. Michael L. Wick, Andrew McCallum, Gerome Miklau
2009	A*	`conf`	Active Learning by Labeling Features. EMNLP Gregory Druck, Burr Settles, Andrew McCallum
2009	—	`ed.`	Advances in Web Mining and Web Usage Analysis, 9th International Workshop on Knowledge Discovery on the Web, WebKDD 2007, and 1st International Workshop on Social Networks Analysis, SNA-KDD 2007, San Jose, CA, USA, August 12-15, 2007. Revised Papers WebKDD/SNAKDD Haizheng Zhang, Myra Spiliopoulou, Bamshad Mobasher, C. Lee Giles, Andrew McCallum, Olfa Nasraoui, Jaideep Srivastava, John Yen
2009	A	`conf`	Alternating Projections for Learning with Expectation Constraints. UAI Kedar Bellare, Gregory Druck, Andrew McCallum
2009	A	`conf`	An Entity Based Model for Coreference Resolution. SDM Michael L. Wick, Aron Culotta, Khashayar Rohanimanesh, Andrew McCallum
2009	—	`conf`	Bi-directional Joint Inference for Entity Resolution and Segmentation Using Imperatively-Defined Factor Graphs. ECML/PKDD (2) Sameer Singh, Karl Schultz, Andrew McCallum
2009	A*	`conf`	Efficient methods for topic model inference on streaming document collections. KDD Limin Yao, David M. Mimno, Andrew McCallum
2009	—	`conf`	FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs. NIPS Andrew McCallum, Karl Schultz, Sameer Singh
2009	A*	`conf`	Generalized Expectation Criteria for Bootstrapping Extractors using Record-Text Alignment. EMNLP Kedar Bellare, Andrew McCallum
2009	B	`conf`	Joint Inference for Natural Language Processing. CoNLL Andrew McCallum
2009	J	`jnl`	Piecewise training for structured prediction. Mach. Learn. Charles Sutton, Andrew McCallum
2009	A*	`conf`	Polylingual Topic Models. EMNLP David M. Mimno, Hanna M. Wallach, Jason Naradowsky, David A. Smith, Andrew McCallum
2009	—	`conf`	Rethinking LDA: Why Priors Matter. NIPS Hanna M. Wallach, David M. Mimno, Andrew McCallum
2009	—	`conf`	Semi-supervised Learning of Dependency Parsers using Generalized Expectation Criteria. ACL/IJCNLP Gregory Druck, Gideon S. Mann, Andrew McCallum
2009	—	`conf`	Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference. NIPS Michael L. Wick, Khashayar Rohanimanesh, Sameer Singh, Andrew McCallum
2008	—	`conf`	A Discriminative Approach to Ontology Mapping. NTII Michael L. Wick, Khashayar Rohanimanesh, Andrew McCallum, AnHai Doan
2008	A*	`conf`	A unified approach for schema matching, coreference and canonicalization. KDD Michael L. Wick, Khashayar Rohanimanesh, Karl Schultz, Andrew McCallum
2008	A*	`conf`	Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields. ACL Gideon S. Mann, Andrew McCallum
2008	—	`conf`	InterNano: e-Science for the Nanomanufacturing Community. eScience Rebecca Reznik-Zellen, Bob Stevens, Michael Thorn, Jeff Morse, Mark D. Smucker, James Allan, David M. Mimno, Andrew McCallum, Mark Tuominen
2008	A*	`conf`	Learning from labeled features using generalized expectation criteria. SIGIR Gregory Druck, Gideon S. Mann, Andrew McCallum
2008	A*	`ed.`	Machine Learning, Proceedings of the Twenty-Fifth International Conference (ICML 2008), Helsinki, Finland, June 5-9, 2008 ICML William W. Cohen, Andrew McCallum, Sam T. Roweis
2008	A	`conf`	Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression. UAI David M. Mimno, Andrew McCallum
2008	A*	`conf`	Unsupervised deduplication using cross-field dependencies. KDD Robert J. Hall, Charles Sutton, Andrew McCallum
2007	A*	`conf`	Canonicalization of database records using adaptive similarity measures. KDD Aron Culotta, Michael L. Wick, Robert J. Hall, Matthew Marzilli, Andrew McCallum
2007	A	`conf`	Cryptogram Decoding for OCR Using Numerization Strings. ICDAR Gary B. Huang, Erik G. Learned-Miller, Andrew McCallum
2007	J	`jnl`	Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data. J. Mach. Learn. Res. Charles Sutton, Andrew McCallum, Khashayar Rohanimanesh
2007	—	`conf`	Efficient Computation of Entropy Gradient for Semi-Supervised Conditional Random Fields. HLT-NAACL (Short Papers) Gideon S. Mann, Andrew McCallum
2007	A*	`conf`	Expertise modeling for matching papers with reviewers. KDD David M. Mimno, Andrew McCallum
2007	—	`conf`	First-Order Probabilistic Models for Coreference Resolution. HLT-NAACL Aron Culotta, Michael L. Wick, Andrew McCallum
2007	A*	`conf`	Generalized component analysis for text with heterogeneous attributes. KDD Xuerui Wang, Chris Pal, Andrew McCallum
2007	A	`conf`	Improved Dynamic Schedules for Belief Propagation. UAI Charles Sutton, Andrew McCallum
2007	A*	`conf`	Improving Author Coreference by Resource-Bounded Information Gathering from the Web. IJCAI Pallika H. Kanani, Andrew McCallum, Chris Pal
2007	—	`conf`	Mining a digital library for influential authors. JCDL David M. Mimno, Andrew McCallum
2007	A*	`conf`	Mixtures of hierarchical topics with Pachinko allocation. ICML David M. Mimno, Wei Li, Andrew McCallum
2007	A	`conf`	Nonparametric Bayes Pachinko Allocation. UAI Wei Li, David M. Blei, Andrew McCallum
2007	—	`conf`	Organizing the OCA: learning faceted subjects from a library of digital books. JCDL David M. Mimno, Andrew McCallum
2007	A*	`conf`	People-LDA: Anchoring Topics to People using Face Recognition. ICCV Vidit Jain, Erik G. Learned-Miller, Andrew McCallum
2007	A*	`conf`	Piecewise pseudolikelihood for efficient training of conditional random fields. ICML Charles Sutton, Andrew McCallum
2007	—	`conf`	Report on the NSF-sponsored Human Language Technology Workshop on Industrial Centers. MTSummit Mary P. Harper, Alex Acero, Srinivas Bangalore, Jaime Carbonell, Jordan Cohen, Barbara Cuthill, Carol Y. Espy-Wilson, Christiane Fellbaum, John Garofolo, Chin-Hui Lee, Jim Lester, Andrew McCallum, Nelson Morgan, Michael Picheney, Joe Picone, Lance Ramshaw, Jeffrey C. Reynar, Hadar Shemtov, Clare Voss
2007	A*	`conf`	Resource-Bounded Information Gathering for Correlation Clustering. COLT Pallika H. Kanani, Andrew McCallum
2007	A*	`conf`	Semi-supervised classification with hybrid generative/discriminative methods. KDD Gregory Druck, Chris Pal, Andrew McCallum, Xiaojin Zhu
2007	A*	`conf`	Simple, robust, scalable semi-supervised learning via expectation regularization. ICML Gideon S. Mann, Andrew McCallum
2007	J	`jnl`	Topic and Role Discovery in Social Networks with Experiments on Enron and Academic Email. J. Artif. Intell. Res. Andrew McCallum, Xuerui Wang, Andrés Corrada-Emmanuel
2007	A*	`conf`	Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval. ICDM Xuerui Wang, Andrew McCallum, Xing Wei
2007	J	`jnl`	WebKDD/SNAKDD 2007: web mining and social network analysis post-workshop report. SIGKDD Explor. Haizheng Zhang, John Yen, C. Lee Giles, Bamshad Mobasher, Myra Spiliopoulou, Jaideep Srivastava, Olfa Nasraoui, Andrew McCallum
2006	—	`conf`	Bibliometric impact measures leveraging topic analysis. JCDL Gideon S. Mann, David M. Mimno, Andrew McCallum
2006	—	`conf`	Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning. ICPR (2) B. Michael Kelm, Chris Pal, Andrew McCallum
2006	J	`jnl`	Corrective feedback and persistent learning for information extraction. Artif. Intell. Aron Culotta, Trausti T. Kristjansson, Andrew McCallum, Paul A. Viola
2006	—	`conf`	Exploring the Use of Conditional Random Field Models and HMMs for Historical Handwritten Document Recognition. DIAL Shaolei Feng, R. Manmatha, Andrew McCallum
2006	J	`jnl`	Information extraction from research papers using conditional random fields. Inf. Process. Manag. Fuchun Peng, Andrew McCallum
2006	A*	`conf`	Information extraction, data mining and joint inference. KDD Andrew McCallum
2006	—	`conf`	Integrating Probabilistic Extraction Models and Data Mining to Discover Relations and Patterns in Text. HLT-NAACL Aron Culotta, Andrew McCallum, Jonathan Betz
2006	—	`conf`	Joint Group and Topic Discovery from Relations and Text. SNA@ICML Andrew McCallum, Xuerui Wang, Natasha Mohanty
2006	A*	`conf`	Learning Field Compatibilities to Extract Database Records from Unstructured Text. EMNLP Michael L. Wick, Aron Culotta, Andrew McCallum
2006	A*	`conf`	Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification. AAAI Andrew McCallum, Chris Pal, Gregory Druck, Xuerui Wang
2006	A*	`conf`	Pachinko allocation: DAG-structured mixture models of topic correlations. ICML Wei Li, Andrew McCallum
2006	—	`conf`	Reducing Weight Undertraining in Structured Discriminative Learning. HLT-NAACL Charles Sutton, Michael Sindelar, Andrew McCallum
2006	—	`ch.`	Semi-Supervised Text Classification Using EM. Semi-Supervised Learning Kamal Nigam, Andrew McCallum, Tom M. Mitchell
2006	—	`conf`	Sparse Forward-Backward Using Minimum Divergence Beams for Fast Training Of Conditional Random Fields. ICASSP (5) Chris Pal, Charles Sutton, Andrew McCallum
2006	J	`jnl`	Table extraction for answer retrieval. Inf. Retr. Xing Wei, W. Bruce Croft, Andrew McCallum
2006	A*	`conf`	Topics over time: a non-Markov continuous-time model of topical trends. KDD Xuerui Wang, Andrew McCallum
2005	A	`conf`	A Conditional Random Field for Discriminatively-trained Finite-state String Edit Distance. UAI Andrew McCallum, Kedar Bellare, Fernando C. N. Pereira
2005	A	`conf`	Collective multi-label classification. CIKM Nadia Ghamrawi, Andrew McCallum
2005	—	`conf`	Composition of Conditional Random Fields for Transfer Learning. HLT/EMNLP Charles Sutton, Andrew McCallum
2005	A	`conf`	Detecting Anomalies in Network Traffic Using Maximum Entropy Estimation. Internet Measurement Conference Yu Gu, Andrew McCallum, Donald F. Towsley
2005	A*	`conf`	Disambiguating Web appearances of people in a social network. WWW Ron Bekkerman, Andrew McCallum
2005	—	`conf`	Group and Topic Discovery from Relations and Their Attributes. NIPS Xuerui Wang, Natasha Mohanty, Andrew McCallum
2005	—	`conf`	Group and topic discovery from relations and text. LinkKDD Xuerui Wang, Natasha Mohanty, Andrew McCallum
2005	J	`jnl`	Information extraction: distilling structured data from unstructured text. ACM Queue Andrew McCallum
2005	B	`conf`	Joint Parsing and Semantic Role Labeling. CoNLL Charles Sutton, Andrew McCallum
2005	A	`conf`	Joint deduplication of multiple record types in relational data. CIKM Aron Culotta, Andrew McCallum
2005	A*	`conf`	Multi-way distributional clustering via pairwise interactions. ICML Ron Bekkerman, Ran El-Yaniv, Andrew McCallum
2005	A	`conf`	Piecewise Training for Undirected Models. UAI Charles Sutton, Andrew McCallum
2005	A*	`conf`	Reducing Labeling Effort for Structured Prediction Tasks. AAAI Aron Culotta, Andrew McCallum
2005	A*	`conf`	Semi-Supervised Sequence Modeling with Syntactic Topic Models. AAAI Wei Li, Andrew McCallum
2005	A*	`conf`	Topic and Role Discovery in Social Networks. IJCAI Andrew McCallum, Andrés Corrada-Emmanuel, Xuerui Wang
2004	—	`conf`	Accurate Information Extraction from Research Papers using Conditional Random Fields. HLT-NAACL Fuchun Peng, Andrew McCallum
2004	A	`conf`	An Integrated, Conditional Model of Information Extraction and Coreference with Appli. UAI Ben Wellner, Andrew McCallum, Fuchun Peng, Michael Hay
2004	B	`conf`	Chinese Segmentation and New Word Detection using Conditional Random Fields. COLING Fuchun Peng, Fangfang Feng, Andrew McCallum
2004	—	`conf`	Conditional Models of Identity Uncertainty with Application to Noun Coreference. NIPS Andrew McCallum, Ben Wellner
2004	—	`conf`	Confidence Estimation for Information Extraction. HLT-NAACL (Short Papers) Aron Culotta, Andrew McCallum
2004	A*	`conf`	Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data. ICML Charles Sutton, Khashayar Rohanimanesh, Andrew McCallum
2004	—	`conf`	Extracting social networks and contact information from email and the Web. CEAS Aron Culotta, Ron Bekkerman, Andrew McCallum
2004	A*	`conf`	Interactive Information Extraction with Constrained Conditional Random Fields. AAAI Trausti T. Kristjansson, Aron Culotta, Paul A. Viola, Andrew McCallum
2003	J	`jnl`	Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002. SIGIR Forum James Allan, Jay Aslam, Nicholas J. Belkin, Chris Buckley, James P. Callan, W. Bruce Croft, Susan T. Dumais, Norbert Fuhr, Donna Harman, David J. Harper, Djoerd Hiemstra, Thomas Hofmann, Eduard H. Hovy, Wessel Kraaij, John D. Lafferty, Victor Lavrenko, David D. Lewis, Liz Liddy, R. Manmatha, Andrew McCallum, Jay M. Ponte, John M. Prager, Dragomir R. Radev, Philip Resnik, Stephen E. Robertson, Ronald Rosenfeld, Salim Roukos, Mark Sanderson, Richard M. Schwartz, Amit Singhal, Alan F. Smeaton, Howard R. Turtle, Ellen M. Voorhees, Ralph M. Weischedel, Jinxi Xu, ChengXiang Zhai
2003	—	`conf`	Classification with Hybrid Generative/Discriminative Models. NIPS Rajat Raina, Yirong Shen, Andrew Y. Ng, Andrew McCallum
2003	B	`conf`	Early results for Named Entity Recognition with Conditional Random Fields, Feature Induction and Web-Enhanced Lexicons. CoNLL Andrew McCallum, Wei Li
2003	A	`conf`	Efficiently Inducing Features of Conditional Random Fields. UAI Andrew McCallum
2003	J	`jnl`	Rapid development of Hindi named entity recognition using conditional random fields and feature induction. ACM Trans. Asian Lang. Inf. Process. Wei Li, Andrew McCallum
2003	—	`conf`	Table Extraction Using Conditional Random Fields. DG.O David Pinto, Andrew McCallum, Xing Wei, W. Bruce Croft
2003	A*	`conf`	Table extraction using conditional random fields. SIGIR David Pinto, Andrew McCallum, Xing Wei, W. Bruce Croft
2003	—	`conf`	Toward Conditional Models of Identity Uncertainty with Application to Proper Noun Coreference. IIWeb Andrew McCallum, Ben Wellner
2001	A*	`conf`	Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. ICML John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira
2001	A*	`conf`	Toward Optimal Active Learning through Sampling Estimation of Error Reduction. ICML Nicholas Roy, Andrew McCallum
2000	A*	`conf`	Efficient clustering of high-dimensional data sets with application to reference matching. KDD Andrew McCallum, Kamal Nigam, Lyle H. Ungar
2000	—	`conf`	Information Extraction with HMM Structures Learned by Stochastic Optimization. AAAI/IAAI Dayne Freitag, Andrew McCallum
2000	A*	`conf`	Learning to Create Customized Authority Lists. ICML Huan Chang, David Cohn, Andrew McCallum
2000	J	`jnl`	Learning to Understand the Web. IEEE Data Eng. Bull. William W. Cohen, Andrew McCallum, Dallan Quass
2000	J	`jnl`	Learning to construct knowledge bases from the World Wide Web. Artif. Intell. Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery
2000	A*	`conf`	Maximum Entropy Markov Models for Information Extraction and Segmentation. ICML Andrew McCallum, Dayne Freitag, Fernando C. N. Pereira
1999	A*	`conf`	A Machine Learning Approach to Building Domain-Specific Search Engines. IJCAI Andrew McCallum, Kamal Nigam, Jason Rennie, Kristie Seymore
1998	A*	`conf`	Improving Text Classification by Shrinkage in a Hierarchy of Classes. ICML Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng
1998	—	`conf`	Learning to Classify Text from Labeled and Unlabeled Documents. AAAI/IAAI Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell
1998	—	`conf`	Learning to Extract Symbolic Knowledge from the World Wide Web. AAAI/IAAI Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery