Explainable Prediction of Medical Codes from Clinical Text. - James Mullenbach; Sarah Wiegreffe; Jon Duke; Jimeng Sun 001; Jacob Eisenstein (NAACL-HLT, 2018)

Clinical Concept Extraction for Document-Level Coding. - Sarah Wiegreffe; Edward Choi; Sherry Yan; Jimeng Sun 001; Jacob Eisenstein (BioNLP@ACL, 2019)

Attention is not not Explanation. - Sarah Wiegreffe; Yuval Pinter (EMNLP/IJCNLP (1), 2019)

Learning to Faithfully Rationalize by Construction. - Sarthak Jain; Sarah Wiegreffe; Yuval Pinter; Byron C. Wallace (ACL, 2020)

Measuring Association Between Labels and Free-Text Rationales. - Sarah Wiegreffe; Ana Marasovic; Noah A. Smith (EMNLP (1), 2021)

Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processing. - Sarah Wiegreffe; Ana Marasovic (NeurIPS Datasets and Benchmarks, 2021)

Teach Me to Explain: A Review of Datasets for Explainable NLP. - Sarah Wiegreffe; Ana Marasovic (CoRR, 2021)

Inferring the Reader: Guiding Automated Story Generation with Commonsense Reasoning. - Xiangyu Peng; Siyan Li; Sarah Wiegreffe; Mark O. Riedl (EMNLP (Findings), 2022)

Calibrating Trust of Multi-Hop Question Answering Systems with Decompositional Probes. - Kaige Xie; Sarah Wiegreffe; Mark O. Riedl (EMNLP (Findings), 2022)

Reframing Human-AI Collaboration for Generating Free-Text Explanations. - Sarah Wiegreffe; Jack Hessel; Swabha Swayamdipta; Mark O. Riedl; Yejin Choi 001 (NAACL-HLT, 2022)

Interpreting Neural Networks for and with Natural Language. - Sarah Wiegreffe (2022)

Editing Common Sense in Transformers. - Anshita Gupta; Debanjan Mondal; Akshay Krishna Sheshadri; Wenlong Zhao 001; Xiang Li 069; Sarah Wiegreffe; Niket Tandon (EMNLP, 2023)

Increasing Probability Mass on Answer Choices Does Not Always Improve Accuracy. - Sarah Wiegreffe; Matthew Finlayson; Oyvind Tafjord; Peter Clark; Ashish Sabharwal (EMNLP, 2023)

Self-Refine: Iterative Refinement with Self-Feedback. - Aman Madaan; Niket Tandon; Prakhar Gupta; Skyler Hallinan; Luyu Gao; Sarah Wiegreffe; Uri Alon 002; Nouha Dziri; Shrimai Prabhumoye; Yiming Yang; Shashank Gupta; Bodhisattwa Prasad Majumder; et al. (NeurIPS, 2023)

Self-Refine: Iterative Refinement with Self-Feedback. - Aman Madaan; Niket Tandon; Prakhar Gupta; Skyler Hallinan; Luyu Gao; Sarah Wiegreffe; Uri Alon 002; Nouha Dziri; Shrimai Prabhumoye; Yiming Yang; Sean Welleck; Bodhisattwa Prasad Majumder; et al. (CoRR, 2023)

Attentiveness to Answer Choices Doesn't Always Entail High QA Accuracy. - Sarah Wiegreffe; Matthew Finlayson; Oyvind Tafjord; Peter Clark; Ashish Sabharwal (CoRR, 2023)

Editing Commonsense Knowledge in GPT. - Anshita Gupta; Debanjan Mondal; Akshay Krishna Sheshadri; Wenlong Zhao 001; Xiang Lorraine Li; Sarah Wiegreffe; Niket Tandon (CoRR, 2023)

The Unreasonable Effectiveness of Easy Training Data for Hard Tasks. - Peter Hase; Mohit Bansal; Peter Clark; Sarah Wiegreffe (ACL (1), 2024)

Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals. - Yanai Elazar; Bhargavi Paranjape; Hao Peng 009; Sarah Wiegreffe; Khyathi Raghavi Chandu; Vivek Srikumar; Sameer Singh 001; Noah A. Smith (EMNLP (Findings), 2024)

Plausibly Problematic Questions in Multiple-Choice Benchmarks for Commonsense Reasoning. - Shramay Palta; Nishant Balepur; Peter Rankel; Sarah Wiegreffe; Marine Carpuat; Rachel Rudinger (EMNLP (Findings), 2024)

The Art of Saying No: Contextual Noncompliance in Language Models. - Faeze Brahman; Sachin Kumar 009; Vidhisha Balachandran; Pradeep Dasigi; Valentina Pyatkin; Abhilasha Ravichander; Sarah Wiegreffe; Nouha Dziri; Khyathi Raghavi Chandu; Jack Hessel; Yulia Tsvetkov; Noah A. Smith; et al. (NeurIPS, 2024)

Answer, Assemble, Ace: Understanding How Transformers Answer Multiple Choice Questions. - Sarah Wiegreffe; Oyvind Tafjord; Yonatan Belinkov; Hannaneh Hajishirzi; Ashish Sabharwal (CoRR, 2024)

Mechanistic? - Naomi Saphra; Sarah Wiegreffe (CoRR, 2024)

On Linear Representations and Pretraining Data Frequency in Language Models. - Jack Merullo; Noah A. Smith; Sarah Wiegreffe; Yanai Elazar (ICLR, 2025)

Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions. - Sarah Wiegreffe; Oyvind Tafjord; Yonatan Belinkov; Hannaneh Hajishirzi; Ashish Sabharwal (ICLR, 2025)

MIB: A Mechanistic Interpretability Benchmark. - Aaron Mueller; Atticus Geiger; Sarah Wiegreffe; Dana Arad; Iván Arcuschin; Adam Belfki; Yik Siu Chan; Jaden Fiotto-Kaufman; Tal Haklay; Michael Hanna 001; Jing Huang; Rohan Gupta; et al. (CoRR, 2025)