Stephen H. Bach

87 papers A* 14A 6B 2C 1Journal 43Unranked 20

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Revisiting Generalization Across Difficulty Levels: It's Not So Easy. EACL (Volume 1: Long Papers) Yeganeh Kordi, Nihal V. Nayak, Max Zuo, Ilana Nguyen, Stephen H. Bach
2026	—	`conf`	Trove: A Flexible Toolkit for Dense Retrieval. EACL (System Demonstrations) Reza Esfandiarpoor, Max Zuo, Stephen H. Bach
2025	A	`conf`	An Adaptive Method for Weak Supervision with Drifting Data. AISTATS Alessio Mazzetto, Reza Esfandiarpoor, Akash Singirikonda, Eli Upfal, Stephen H. Bach
2025	—	`conf`	Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance. EMNLP (Findings) Reza Esfandiarpoor, George Zerveas, Ruochen Zhang, Macton Mgonzo, Carsten Eickhoff, Stephen H. Bach
2025	J	`jnl`	Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance. CoRR Reza Esfandiarpoor, George Zerveas, Ruochen Zhang, Macton Mgonzo, Carsten Eickhoff, Stephen H. Bach
2025	J	`jnl`	Can We Predict Alignment Before Models Finish Thinking? Towards Monitoring Misaligned Reasoning Models. CoRR Yik Siu Chan, Zheng-Xin Yong, Stephen H. Bach
2025	J	`jnl`	Crosslingual Reasoning through Test-Time Scaling. CoRR Zheng-Xin Yong, Muhammad Farid Adilazuarda, Jonibek Mansurov, Ruochen Zhang, Niklas Muennighoff, Carsten Eickhoff, Genta Indra Winata, Julia Kreutzer, Stephen H. Bach, Alham Fikri Aji
2025	—	`conf`	K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction. KDD (2) Tassallah Abdullahi, Ioanna Gemou, Nihal V. Nayak, Ghulam Murtaza, Stephen H. Bach, Carsten Eickhoff, Ritambhara Singh
2025	J	`jnl`	K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction. CoRR Tassallah Abdullahi, Ioanna Gemou, Nihal V. Nayak, Ghulam Murtaza, Stephen H. Bach, Carsten Eickhoff, Ritambhara Singh
2025	—	`conf`	Planetarium: A Rigorous Benchmark for Translating Text to Structured Planning Languages. NAACL (Long Papers) Max Zuo, Francisco Piedrahita Velez, Xiaochen Li, Michael Littman, Stephen H. Bach
2025	J	`jnl`	Revisiting Generalization Across Difficulty Levels: It's Not So Easy. CoRR Yeganeh Kordi, Nihal V. Nayak, Max Zuo, Ilana Nguyen, Stephen H. Bach
2025	J	`jnl`	Self-Jailbreaking: Language Models Can Reason Themselves Out of Safety Alignment After Benign Reasoning Training. CoRR Zheng-Xin Yong, Stephen H. Bach
2025	A*	`conf`	The State of Multilingual LLM Safety Research: From Measuring The Language Gap To Mitigating It. EMNLP Zheng Xin Yong, Beyza Ermis, Marzieh Fadaee, Stephen H. Bach, Julia Kreutzer
2025	J	`jnl`	The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It. CoRR Zheng-Xin Yong, Beyza Ermis, Marzieh Fadaee, Stephen H. Bach, Julia Kreutzer
2025	J	`jnl`	TheMCPCompany: Creating General-purpose Agents with Task-specific Tools. CoRR Reza Esfandiarpoor, Vishwas Suryanarayanan, Stephen H. Bach, Vishal Chowdhary, Anthony Aue
2025	J	`jnl`	Trove: A Flexible Toolkit for Dense Retrieval. CoRR Reza Esfandiarpoor, Max Zuo, Stephen H. Bach
2024	J	`jnl`	$100K or 100 Days: Trade-offs when Pre-Training with Academic Resources. CoRR Apoorv Khandelwal, Tian Yun, Nihal V. Nayak, Jack Merullo, Stephen H. Bach, Chen Sun, Ellie Pavlick
2024	—	`conf`	Does CLIP Bind Concepts? Probing Compositionality in Large Image Models. EACL (Findings) Martha Lewis, Nihal V. Nayak, Peilin Yu, Jack Merullo, Qinan Yu, Stephen H. Bach, Ellie Pavlick
2024	A*	`conf`	Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification. ICLR Reza Esfandiarpoor, Stephen H. Bach
2024	A*	`conf`	If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions. EMNLP Reza Esfandiarpoor, Cristina Menghini, Stephen H. Bach
2024	J	`jnl`	If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions. CoRR Reza Esfandiarpoor, Cristina Menghini, Stephen H. Bach
2024	—	`conf`	Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation. ACL (Findings) Nihal V. Nayak, Yiyang Nan, Avi Trost, Stephen H. Bach
2024	J	`jnl`	Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation. CoRR Nihal V. Nayak, Yiyang Nan, Avi Trost, Stephen H. Bach
2024	J	`jnl`	Leveraging Large Language Models for Structure Learning in Prompted Weak Supervision. CoRR Jinyan Su, Peilin Yu, Jieyu Zhang, Stephen H. Bach
2024	—	`conf`	LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons. EMNLP (Findings) Zheng Xin Yong, Cristina Menghini, Stephen H. Bach
2024	J	`jnl`	LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons. CoRR Zheng Xin Yong, Cristina Menghini, Stephen H. Bach
2024	J	`jnl`	Planetarium: A Rigorous Benchmark for Translating Text to Structured Planning Languages. CoRR Max Zuo, Francisco Piedrahita Velez, Xiaochen Li, Michael L. Littman, Stephen H. Bach
2024	—	`conf`	Preference Tuning For Toxicity Mitigation Generalizes Across Languages. EMNLP (Findings) Xiaochen Li, Zheng Xin Yong, Stephen H. Bach
2024	J	`jnl`	Preference Tuning For Toxicity Mitigation Generalizes Across Languages. CoRR Xiaochen Li, Zheng-Xin Yong, Stephen H. Bach
2023	—	`conf`	Alfred: A System for Prompted Weak Supervision. ACL (demo) Peilin Yu, Stephen H. Bach
2023	J	`jnl`	Alfred: A System for Prompted Weak Supervision. CoRR Peilin Yu, Stephen H. Bach
2023	J	`jnl`	An Adaptive Method for Weak Supervision with Drifting Data. CoRR Alessio Mazzetto, Reza Esfandiarpoor, Eli Upfal, Stephen H. Bach
2023	A*	`conf`	Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning. NeurIPS Cristina Menghini, Andrew Delworth, Stephen H. Bach
2023	J	`jnl`	Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning. CoRR Cristina Menghini, Andrew Delworth, Stephen H. Bach
2023	J	`jnl`	Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification. CoRR Reza Esfandiarpoor, Stephen H. Bach
2023	A*	`conf`	Learning to Compose Soft Prompts for Compositional Zero-Shot Learning. ICLR Nihal V. Nayak, Peilin Yu, Stephen H. Bach
2023	B	`conf`	Leveraging Large Language Models for Structure Learning in Prompted Weak Supervision. IEEE Big Data Jinyan Su, Peilin Yu, Jieyu Zhang, Stephen H. Bach
2023	J	`jnl`	Low-Resource Languages Jailbreak GPT-4. CoRR Zheng Xin Yong, Cristina Menghini, Stephen H. Bach
2022	J	`jnl`	BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing. CoRR Jason Alan Fries, Leon Weber, Natasha Seelam, Gabriel Altay, Debajyoti Datta, Samuele Garda, Myungsun Kang, Ruisi Su, Wojciech Kusa, Samuel Cahyawijaya, Fabio Barth, Simon Ott, Matthias Samwald, Stephen H. Bach, Stella Biderman, Mario Sänger, Bo Wang, Alison Callahan, Daniel León Periñán, Théo Gigant, Patrick Haller, Jenny Chim, José David Posada, John Michael Giorgi, Karthik Rangasai Sivaraman, Marc Pàmies, Marianna Nezhurina, Robert Martin, Michael Cullan, Moritz Freidank, Nathan Dahlberg, Shubhanshu Mishra, Shamik Bose, Nicholas Michio Broad, Yanis Labrak, Shlok S. Deshmukh, Sid Kiblawi, Ayush Singh, Minh Chien Vu, Trishala Neeraj, Jonas Golde, Albert Villanova del Moral, Benjamin Beilharz
2022	A*	`conf`	BigBio: A Framework for Data-Centric Biomedical Natural Language Processing. NeurIPS Jason A. Fries, Leon Weber, Natasha Seelam, Gabriel Altay, Debajyoti Datta, Samuele Garda, Sunny Kang, Rosaline Su, Wojciech Kusa, Samuel Cahyawijaya, Fabio Barth, Simon Ott, Matthias Samwald, Stephen H. Bach, Stella Biderman, Mario Sänger, Bo Wang, Alison Callahan, Daniel León Periñán, Théo Gigant, Patrick Haller, Jenny Chim, José D. Posada, John M. Giorgi, Karthik Rangasai Sivaraman, Marc Pàmies, Marianna Nezhurina, Robert Martin, Michael Cullan, Moritz Freidank, Nathan Dahlberg, Shubhanshu Mishra, Shamik Bose, Nicholas Broad, Yanis Labrak, Shlok Deshmukh, Sid Kiblawi, Ayush Singh, Minh Chien Vu, Trishala Neeraj, Jonas Golde, Albert Villanova del Moral, Benjamin Beilharz
2022	C	`conf`	Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations. AIES Jessica Dai, Sohini Upadhyay, Ulrich Aïvodji, Stephen H. Bach, Himabindu Lakkaraju
2022	J	`jnl`	Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations. CoRR Jessica Dai, Sohini Upadhyay, Ulrich Aïvodji, Stephen H. Bach, Himabindu Lakkaraju
2022	J	`jnl`	Language Models in the Loop: Incorporating Prompting into Weak Supervision. CoRR Ryan Smith, Jason A. Fries, Braden Hancock, Stephen H. Bach
2022	A	`conf`	Learning from Multiple Noisy Partial Labelers. AISTATS Peilin Yu, Tiffany Ding, Stephen H. Bach
2022	J	`jnl`	Learning to Compose Soft Prompts for Compositional Zero-Shot Learning. CoRR Nihal V. Nayak, Peilin Yu, Stephen H. Bach
2022	A*	`conf`	Multitask Prompted Training Enables Zero-Shot Task Generalization. ICLR Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, Alexander M. Rush
2022	—	`conf`	PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts. ACL (demo) Stephen H. Bach, Victor Sanh, Zheng Xin Yong, Albert Webson, Colin Raffel, Nihal V. Nayak, Abheesht Sharma, Taewoon Kim, M. Saiful Bari, Thibault Févry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Alan Fries, Maged Saeed AlShaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Dragomir R. Radev, Mike Tian-Jian Jiang, Alexander M. Rush
2022	J	`jnl`	PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts. CoRR Stephen H. Bach, Victor Sanh, Zheng Xin Yong, Albert Webson, Colin Raffel, Nihal V. Nayak, Abheesht Sharma, Taewoon Kim, M. Saiful Bari, Thibault Févry, Zaid Alyafeai, Manan Dey, Andrea Santilli, Zhiqing Sun, Srulik Ben-David, Canwen Xu, Gunjan Chhablani, Han Wang, Jason Alan Fries, Maged Saeed AlShaibani, Shanya Sharma, Urmish Thakker, Khalid Almubarak, Xiangru Tang, Mike Tian-Jian Jiang, Alexander M. Rush
2022	—	`conf`	TAGLETS: A System for Automatic Semi-Supervised Learning with Auxiliary Data. MLSys Wasu Piriyakulkij, Cristina Menghini, Ross Briden, Nihal V. Nayak, Jeffrey Zhu, Elaheh Raisi, Stephen H. Bach
2022	A*	`conf`	Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes. NeurIPS Alessio Mazzetto, Cristina Menghini, Andrew Yuan, Eli Upfal, Stephen H. Bach
2022	J	`jnl`	Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes. CoRR Alessio Mazzetto, Cristina Menghini, Andrew Yuan, Eli Upfal, Stephen H. Bach
2022	J	`jnl`	Zero-Shot Learning with Common Sense Knowledge Graphs. Trans. Mach. Learn. Res. Nihal V. Nayak, Stephen H. Bach
2021	A*	`conf`	Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees. ICML Alessio Mazzetto, Cyrus Cousins, Dylan Sam, Stephen H. Bach, Eli Upfal
2021	J	`jnl`	Learning from Multiple Noisy Partial Labelers. CoRR Peilin Yu, Tiffany Ding, Stephen H. Bach
2021	J	`jnl`	Multitask Prompted Training Enables Zero-Shot Task Generalization. CoRR Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M. Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, Alexander M. Rush
2021	A	`conf`	Semi-Supervised Aggregation of Dependent Weak Supervision Sources With Performance Guarantees. AISTATS Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, Stephen H. Bach
2021	J	`jnl`	TAGLETS: A System for Automatic Semi-Supervised Learning with Auxiliary Data. CoRR Wasu Piriyakulkij, Cristina Menghini, Ross Briden, Nihal V. Nayak, Jeffrey Zhu, Elaheh Raisi, Stephen H. Bach
2021	J	`jnl`	What will it take to generate fairness-preserving explanations? CoRR Jessica Dai, Sohini Upadhyay, Stephen H. Bach, Himabindu Lakkaraju
2020	J	`jnl`	Pseudo Shots: Few-Shot Learning with Auxiliary Data. CoRR Reza Esfandiarpoor, Mohsen Hajabdollahi, Stephen H. Bach
2020	—	`conf`	Selecting Auxiliary Data Using Knowledge Graphs for Image Classification with Limited Labels. CVPR Workshops Elaheh Raisi, Stephen H. Bach
2020	J	`jnl`	Snorkel: rapid training data creation with weak supervision. VLDB J. Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason A. Fries, Sen Wu, Christopher Ré
2020	A*	`conf`	Weakly Supervised Sequence Tagging from Noisy Rules. AAAI Esteban Safranchik, Shiying Luo, Stephen H. Bach
2020	J	`jnl`	Zero-Shot Learning with Common Sense Knowledge Graphs. CoRR Nihal V. Nayak, Stephen H. Bach
2019	—	`conf`	Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale. SIGMOD Conference Stephen H. Bach, Daniel Rodriguez, Yintao Liu, Chong Luo, Haidong Shao, Cassandra Xia, Souvik Sen, Alexander Ratner, Braden Hancock, Houman Alborzi, Rahul Kuchhal, Christopher Ré, Rob Malkin
2018	J	`jnl`	Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale. CoRR Stephen H. Bach, Daniel Rodriguez, Yintao Liu, Chong Luo, Haidong Shao, Cassandra Xia, Souvik Sen, Alexander Ratner, Braden Hancock, Houman Alborzi, Rahul Kuchhal, Christopher Ré, Rob Malkin
2017	J	`jnl`	Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. J. Mach. Learn. Res. Stephen H. Bach, Matthias Broecheler, Bert Huang, Lise Getoor
2017	A*	`conf`	Learning the Structure of Generative Models without Labeled Data. ICML Stephen H. Bach, Bryan Dawei He, Alexander Ratner, Christopher Ré
2017	J	`jnl`	Learning the Structure of Generative Models without Labeled Data. CoRR Stephen H. Bach, Bryan Dawei He, Alexander Ratner, Christopher Ré
2017	A	`conf`	Snorkel: A System for Lightweight Extraction. CIDR Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason Alan Fries, Sen Wu, Christopher Ré
2017	—	`conf`	Snorkel: Fast Training Set Generation for Information Extraction. SIGMOD Conference Alexander J. Ratner, Stephen H. Bach, Henry R. Ehrenberg, Christopher Ré
2017	J	`jnl`	Snorkel: Rapid Training Data Creation with Weak Supervision. CoRR Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason Alan Fries, Sen Wu, Christopher Ré
2017	J	`jnl`	Snorkel: Rapid Training Data Creation with Weak Supervision. Proc. VLDB Endow. Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason Alan Fries, Sen Wu, Christopher Ré
2017	J	`jnl`	Soft quantification in statistical relational learning. Mach. Learn. Golnoosh Farnadi, Stephen H. Bach, Marie-Francine Moens, Lise Getoor, Martine De Cock
2016	A*	`conf`	Interpretable Decision Sets: A Joint Framework for Description and Prediction. KDD Himabindu Lakkaraju, Stephen H. Bach, Jure Leskovec
2015	J	`jnl`	Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. CoRR Stephen H. Bach, Matthias Broecheler, Bert Huang, Lise Getoor
2015	—	`—`	Hinge-Loss Markov Random Fields and Probabilistic Soft Logic: A Scalable Approach to Structured Prediction. Stephen H. Bach
2015	A*	`conf`	Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs. ICML Stephen H. Bach, Bert Huang, Jordan L. Boyd-Graber, Lise Getoor
2015	B	`conf`	Statistical Relational Learning with Soft Quantifiers. ILP Golnoosh Farnadi, Stephen H. Bach, Marjon Blondeel, Marie-Francine Moens, Lise Getoor, Martine De Cock
2015	A	`conf`	Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees. AISTATS Stephen H. Bach, Bert Huang, Lise Getoor
2014	—	`conf`	Extending PSL with Fuzzy Quantifiers. StarAI@AAAI Golnoosh Farnadi, Stephen H. Bach, Marie-Francine Moens, Lise Getoor, Martine De Cock
2013	—	`conf`	Collective Activity Detection Using Hinge-loss Markov Random Fields. CVPR Workshops Ben London, Sameh Khamis, Stephen H. Bach, Bert Huang, Lise Getoor, Larry S. Davis
2013	A	`conf`	Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. UAI Stephen H. Bach, Bert Huang, Ben London, Lise Getoor
2013	J	`jnl`	Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. CoRR Stephen H. Bach, Bert Huang, Ben London, Lise Getoor
2012	—	`conf`	Graph Summarization in Annotated Data Using Probabilistic Soft Logic. URSW Alex Memory, Angelika Kimmig, Stephen H. Bach, Louiqa Raschid, Lise Getoor
2012	—	`conf`	Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization. NIPS Stephen H. Bach, Matthias Broecheler, Lise Getoor, Dianne P. O'Leary
2010	—	`conf`	A Bayesian Approach to Concept Drift. NIPS Stephen H. Bach, Marcus A. Maloof
2008	A*	`conf`	Paired Learners for Concept Drift. ICDM Stephen H. Bach, Marcus A. Maloof