DynaMiTE: Discovering Explosive Topic Evolutions with User Guidance. - Nishant Balepur; Shivam Agarwal; Karthik Venkat Ramanan; Susik Yoon; Diyi Yang; Jiawei Han 001 (ACL (Findings), 2023)

Text Fact Transfer. - Nishant Balepur; Jie Huang 009; Kevin Chen-Chuan Chang (EMNLP, 2023)

Expository Text Generation: Imitate, Retrieve, Paraphrase. - Nishant Balepur; Jie Huang 009; Kevin Chen-Chuan Chang (EMNLP, 2023)

Mastering the ABCDs of Complex Questions: Answer-Based Claim Decomposition for Fine-grained Self-Evaluation. - Nishant Balepur; Jie Huang 009; Samraj Moorjani; Hari Sundaram; Kevin Chen-Chuan Chang (CoRR, 2023)

It's Not Easy Being Wrong: Evaluating Process of Elimination Reasoning in Large Language Models. - Nishant Balepur; Shramay Palta; Rachel Rudinger (CoRR, 2023)

It's Not Easy Being Wrong: Large Language Models Struggle with Process of Elimination Reasoning. - Nishant Balepur; Shramay Palta; Rachel Rudinger (ACL (Findings), 2024)

Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question? - Nishant Balepur; Abhilasha Ravichander; Rachel Rudinger (ACL (1), 2024)

A SMART Mnemonic Sounds like "Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic Learning Stick. - Nishant Balepur; Matthew Shu; Alexander Miserlis Hoyle; Alison Robey; Shi Feng 005; Seraphina Goldfarb-Tarrant; Jordan L. Boyd-Graber (EMNLP, 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)

KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students. - Matthew Shu; Nishant Balepur; Shi Feng 005; Jordan L. Boyd-Graber (EMNLP, 2024)

The Prompt Report: A Systematic Survey of Prompting Techniques. - Sander Schulhoff; Michael Ilie; Nishant Balepur; Konstantine Kahadze; Amanda Liu; Chenglei Si; Yinheng Li; Aayush Gupta; HyoJung Han; Sevien Schulhoff; Pranav Sandeep Dulepet; Saurav Vidyadhara; et al. (CoRR, 2024)

Is Your Large Language Model Knowledgeable or a Choices-Only Cheater? - Nishant Balepur; Rachel Rudinger (CoRR, 2024)

Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personas. - Nishant Balepur; Vishakh Padmakumar; Fumeng Yang; Shi Feng 005; Rachel Rudinger; Jordan Lee Boyd-Graber (ACL (1), 2025)

Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above. - Nishant Balepur; Rachel Rudinger; Jordan Lee Boyd-Graber (ACL (1), 2025)

Reverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer? - Nishant Balepur; Feng Gu; Abhilasha Ravichander; Shi Feng 005; Jordan Lee Boyd-Graber; Rachel Rudinger (NAACL (Short Papers), 2025)

MoDS: Moderating a Mixture of Document Speakers to Summarize Debatable Queries in Document Collections. - Nishant Balepur; Alexa F. Siu; Nedim Lipka; Franck Dernoncourt; Tong Sun 005; Jordan Lee Boyd-Graber; Puneet Mathur (NAACL (Long Papers), 2025)