Matthew R. Gormley

47 papers A* 2Journal 25Unranked 20

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	From sunblock to softblock: Analyzing the correlates of neology in published writing and on social media. CoRR Maria Ryskina, Matthew R. Gormley, Kyle Mahowald, David R. Mortensen, Taylor Berg-Kirkpatrick, Vivek Kulkarni
2025	—	`conf`	In-Context Learning with Long-Context Models: An In-Depth Exploration. NAACL (Long Papers) Amanda Bertsch, Maor Ivgi, Emily Xiao, Uri Alon, Jonathan Berant, Matthew R. Gormley, Graham Neubig
2025	—	`conf`	Larger than Life In-Class Demonstrations for Introductory Machine Learning. SIGCSE (1) Henry Chai, Matthew R. Gormley
2025	J	`jnl`	Oolong: Evaluating Long Context Reasoning and Aggregation Capabilities. CoRR Amanda Bertsch, Adithya Pratapa, Teruko Mitamura, Graham Neubig, Matthew R. Gormley
2025	J	`jnl`	Predicting the Past: Estimating Historical Appraisals with OCR and Machine Learning. CoRR Mihir Bhaskar, Jun Tao Luo, Zihan Geng, Asmita Hajra, Junia Howell, Matthew R. Gormley
2024	J	`jnl`	A Taxonomy for Data Contamination in Large Language Models. CoRR Medha Palavalli, Amanda Bertsch, Matthew R. Gormley
2024	J	`jnl`	In-Context Learning with Long-Context Models: An In-Depth Exploration. CoRR Amanda Bertsch, Maor Ivgi, Uri Alon, Jonathan Berant, Matthew R. Gormley, Graham Neubig
2023	J	`jnl`	It's MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk. CoRR Amanda Bertsch, Alex Xie, Graham Neubig, Matthew R. Gormley
2023	J	`jnl`	Learning Mutually Informed Representations for Characters and Subwords. CoRR Yilin Wang, Xinyi Hu, Matthew R. Gormley
2023	J	`jnl`	MDACE: MIMIC Documents Annotated with Code Evidence. CoRR Hua Cheng, Rana Jafari, April Russell, Russell Klopfer, Edmond Lu, Benjamin Striner, Matthew R. Gormley
2023	J	`jnl`	SummQA at MEDIQA-Chat 2023: In-Context Learning with GPT-4 for Medical Summarization. CoRR Yash Mathur, Sanketh Rangreji, Raghav Kapoor, Medha Palavalli, Amanda Bertsch, Matthew R. Gormley
2023	J	`jnl`	Unlimiformer: Long-Range Transformers with Unlimited Length Input. CoRR Amanda Bertsch, Uri Alon, Graham Neubig, Matthew R. Gormley
2022	J	`jnl`	AdaFocal: Calibration-aware Adaptive Focal Loss. CoRR Arindam Ghosh, Thomas Schaaf, Matthew R. Gormley
2022	—	`conf`	He Said, She Said: Style Transfer for Shifting the Perspective of Dialogues. EMNLP (Findings) Amanda Bertsch, Graham Neubig, Matthew R. Gormley
2022	J	`jnl`	He Said, She Said: Style Transfer for Shifting the Perspective of Dialogues. CoRR Amanda Bertsch, Graham Neubig, Matthew R. Gormley
2022	J	`jnl`	On Efficiently Acquiring Annotations for Multilingual Models. CoRR Joel Ruben Antony Moniz, Barun Patra, Matthew R. Gormley
2022	J	`jnl`	Revisiting text decomposition methods for NLI-based factuality scoring of summaries. CoRR John Glover, Federico Fancellu, Vasudevan Jagannathan, Matthew R. Gormley, Thomas Schaaf
2021	J	`jnl`	Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction. CoRR Maria Ryskina, Eduard H. Hovy, Taylor Berg-Kirkpatrick, Matthew R. Gormley
2021	—	`conf`	Effective Convolutional Attention Network for Multi-label Clinical Document Classification. EMNLP (1) Yang Liu, Hua Cheng, Russell Klopfer, Matthew R. Gormley, Thomas Schaaf
2021	—	`conf`	Leveraging Pretrained Models for Automatic Summarization of Doctor-Patient Conversations. EMNLP (Findings) Longxiang Zhang, Renato Negrinho, Arindam Ghosh, Vasudevan Jagannathan, Hamid Reza Hassanzadeh, Thomas Schaaf, Matthew R. Gormley
2021	J	`jnl`	Leveraging Pretrained Models for Automatic Summarization of Doctor-Patient Conversations. CoRR Longxiang Zhang, Renato Negrinho, Arindam Ghosh, Vasudevan Jagannathan, Hamid Reza Hassanzadeh, Thomas Schaaf, Matthew R. Gormley
2021	—	`conf`	Limitations of Autoregressive Models and Their Alternatives. NAACL-HLT Chu-Cheng Lin, Aaron Jaech, Xin Li, Matthew R. Gormley, Jason Eisner
2020	—	`conf`	An Empirical Investigation of Beam-Aware Training in Supertagging. EMNLP (Findings) Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon
2020	J	`jnl`	An Empirical Investigation of Beam-Aware Training in Supertagging. CoRR Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon
2020	J	`jnl`	Autoregressive Modeling is Misspecified for Some Sequence Distributions. CoRR Chu-Cheng Lin, Aaron Jaech, Xin Li, Matthew R. Gormley, Jason Eisner
2020	A*	`conf`	Phonetic and Visual Priors for Decipherment of Informal Romanization. ACL Maria Ryskina, Matthew R. Gormley, Taylor Berg-Kirkpatrick
2020	J	`jnl`	Phonetic and Visual Priors for Decipherment of Informal Romanization. CoRR Maria Ryskina, Matthew R. Gormley, Taylor Berg-Kirkpatrick
2020	—	`conf`	Training for Gibbs Sampling on Conditional Random Fields with Neural Scoring Factors. EMNLP (1) Sida Gao, Matthew R. Gormley
2019	—	`conf`	Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces. ACL (1) Barun Patra, Joel Ruben Antony Moniz, Sarthak Garg, Matthew R. Gormley, Graham Neubig
2019	J	`jnl`	Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces. CoRR Barun Patra, Joel Ruben Antony Moniz, Sarthak Garg, Matthew R. Gormley, Graham Neubig
2019	—	`conf`	Neural Finite-State Transducers: Beyond Rational Relations. NAACL-HLT (1) Chu-Cheng Lin, Hao Zhu, Matthew R. Gormley, Jason Eisner
2018	J	`jnl`	Learning Beam Search Policies via Imitation Learning. CoRR Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon
2018	—	`conf`	Neural Factor Graph Models for Cross-lingual Morphological Tagging. ACL (1) Chaitanya Malaviya, Matthew R. Gormley, Graham Neubig
2018	J	`jnl`	Neural Factor Graph Models for Cross-lingual Morphological Tagging. CoRR Chaitanya Malaviya, Matthew R. Gormley, Graham Neubig
2016	—	`conf`	Embedding Lexical Features via Low-Rank Tensors. HLT-NAACL Mo Yu, Mark Dredze, Raman Arora, Matthew R. Gormley
2015	—	`conf`	A Concrete Chinese NLP Pipeline. HLT-NAACL Nanyun Peng, Francis Ferraro, Mo Yu, Nicholas Andrews, Jay DeYoung, Max Thomas, Matthew R. Gormley, Travis Wolfe, Craig Harman, Benjamin Van Durme, Mark Dredze
2015	J	`jnl`	Approximation-Aware Dependency Parsing by Belief Propagation. CoRR Matthew R. Gormley, Mark Dredze, Jason Eisner
2015	J	`jnl`	Approximation-Aware Dependency Parsing by Belief Propagation. Trans. Assoc. Comput. Linguistics Matthew R. Gormley, Mark Dredze, Jason Eisner
2015	—	`conf`	Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction. HLT-NAACL Mo Yu, Matthew R. Gormley, Mark Dredze
2015	A*	`conf`	Improved Relation Extraction with Feature-Rich Compositional Embedding Models. EMNLP Matthew R. Gormley, Mo Yu, Mark Dredze
2015	J	`jnl`	Improved Relation Extraction with Feature-rich Compositional Embedding Models. CoRR Matthew R. Gormley, Mo Yu, Mark Dredze
2015	—	`conf`	Structured Belief Propagation for NLP. ACL (Tutorial Abstracts) Matthew R. Gormley, Jason Eisner
2014	—	`conf`	Low-Resource Semantic Role Labeling. ACL (1) Matthew R. Gormley, Margaret Mitchell, Benjamin Van Durme, Mark Dredze
2013	—	`conf`	Nonconvex Global Optimization for Latent-Variable Models. ACL (1) Matthew R. Gormley, Jason Eisner
2012	—	`conf`	Entity Clustering Across Languages. HLT-NAACL Spence Green, Nicholas Andrews, Matthew R. Gormley, Mark Dredze, Christopher D. Manning
2012	—	`conf`	Shared Components Topic Models. HLT-NAACL Matthew R. Gormley, Mark Dredze, Benjamin Van Durme, Jason Eisner
2010	—	`conf`	Non-Expert Correction of Automatically Generated Relation Annotations. Mturk@HLT-NAACL Matthew R. Gormley, Adam Gerber, Mary P. Harper, Mark Dredze