Nishant Balepur

According to our database, Nishant Balepur authored at least 24 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute.

Nishant Balepur, Malachi Hamada, Varsha Kishore, Sergey Feldman, Amanpreet Singh, Pao Siangliulue, Joseph Chee Chang, Rachel Rudinger, Eunsol Choi, Jordan Lee Boyd-Graber, Doug Downey, Aakanksha Naik

CoRR, April, 2026

Measuring User's Mental Models of Speech Translation in Human-AI Collaboration.

Hyojung Han, Nishant Balepur, Jordan Lee Boyd-Graber, Marine Carpuat

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

BenchMarker: An Education-Inspired Toolkit for Highlighting Flaws in Multiple-Choice Benchmarks.

Nishant Balepur, Bhavya Rajasekaran, Hyunjin Jane Oh, Michael Xie, Atrey Desai, Vipul Gupta, Steven James Moore, Eunsol Choi, Rachel Rudinger, Jordan Lee Boyd-Graber

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users.

Nishant Balepur, Malachi Hamada, Varsha Kishore, Sergey Feldman, Amanpreet Singh, Pao Siangliulue, Joseph Chee Chang, Eunsol Choi, Jordan Lee Boyd-Graber, Aakanksha Naik

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite.

Jonathan Bragg, Mike D'Arcy, Nishant Balepur, Dan Bareket, Bhavana Dalvi, Sergey Feldman, Dany Haddad, Jena D. Hwang, Peter A. Jansen, Varsha Kishore, Bodhisattwa Prasad Majumder, Aakanksha Naik, Sigal Rahamimov, Kyle Richardson, Amanpreet Singh, Harshit Surana, Aryeh Tiktinsky, Rosni Vasu, Guy Wiener, Chloe Anastasiades, Stefan Candra, Jason Dunkelberger, Dan Emery, Rob Evans, Malachi Hamada, Regan Huff, Rodney Kinney, Matt Latzke, Jaron Lochner, Ruben Lozano-Aguilera, Cecile Nguyen, Smita Rao, Amber Tanaka, Brooke Vlahos, Peter Clark, Doug Downey, Yoav Goldberg, Ashish Sabharwal, Daniel S. Weld

CoRR, October, 2025

Can They Dixit? Yes they Can! Dixit as a Playground for Multimodal Language Model Capabilities.

Nishant Balepur, Dang Nguyen, Dayeon Ki

CoRR, October, 2025

Test-Time Reasoners Are Strategic Multiple-Choice Test-Takers.

Nishant Balepur, Atrey Desai, Rachel Rudinger

CoRR, October, 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, Jordan Lee Boyd-Graber, Puneet Mathur

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 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, Jordan Lee Boyd-Graber, Rachel Rudinger

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

A Good Plan is Hard to Find: Aligning Models with Preferences is Misaligned with What Helps Users.

Nishant Balepur, Matthew Shu, Yoo Yeon Sung, Seraphina Goldfarb-Tarrant, Shi Feng, Fumeng Yang, Rachel Rudinger, Jordan Lee Boyd-Graber

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 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

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personas.

Nishant Balepur, Vishakh Padmakumar, Fumeng Yang, Shi Feng, Rachel Rudinger, Jordan Lee Boyd-Graber

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Is Your Large Language Model Knowledgeable or a Choices-Only Cheater?

Nishant Balepur, Rachel Rudinger

CoRR, 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, Dayeon Ki, Sweta Agrawal, Chau Pham, Gerson C. Kroiz, Feileen Li, Hudson Tao, Ashay Srivastava, Hevander Da Costa, Saloni Gupta, Megan L. Rogers, Inna Goncearenco, Giuseppe Sarli, Igor Galynker, Denis Peskoff, Marine Carpuat, Jules White, Shyamal Anadkat, Alexander Miserlis Hoyle, Philip Resnik

CoRR, 2024

KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students.

Matthew Shu, Nishant Balepur, Shi Feng, Jordan L. Boyd-Graber

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Plausibly Problematic Questions in Multiple-Choice Benchmarks for Commonsense Reasoning.

Shramay Palta, Nishant Balepur, Peter Rankel, Sarah Wiegreffe, Marine Carpuat, Rachel Rudinger

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 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, Seraphina Goldfarb-Tarrant, Jordan L. Boyd-Graber

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?

Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

It's Not Easy Being Wrong: Large Language Models Struggle with Process of Elimination Reasoning.

Nishant Balepur, Shramay Palta, Rachel Rudinger

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

It's Not Easy Being Wrong: Evaluating Process of Elimination Reasoning in Large Language Models.

Nishant Balepur, Shramay Palta, Rachel Rudinger

CoRR, 2023

Mastering the ABCDs of Complex Questions: Answer-Based Claim Decomposition for Fine-grained Self-Evaluation.

Nishant Balepur, Jie Huang, Samraj Moorjani, Hari Sundaram, Kevin Chen-Chuan Chang

CoRR, 2023

Expository Text Generation: Imitate, Retrieve, Paraphrase.

Nishant Balepur, Jie Huang, Kevin Chen-Chuan Chang

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Text Fact Transfer.

Nishant Balepur, Jie Huang, Kevin Chen-Chuan Chang

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

DynaMiTE: Discovering Explosive Topic Evolutions with User Guidance.

Nishant Balepur, Shivam Agarwal, Karthik Venkat Ramanan, Susik Yoon, Diyi Yang, Jiawei Han

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023