Unsupervised Extractive Summarization using Pointwise Mutual Information. - Vishakh Padmakumar; He He 001 (EACL, 2021)

BBQ: A hand-built bias benchmark for question answering. - Alicia Parrish; Angelica Chen; Nikita Nangia; Vishakh Padmakumar; Jason Phang; Jana Thompson; Phu Mon Htut; Samuel R. Bowman (ACL (Findings), 2022)

Help me write a Poem - Instruction Tuning as a Vehicle for Collaborative Poetry Writing. - Tuhin Chakrabarty; Vishakh Padmakumar; He He 001 (EMNLP, 2022)

Machine-in-the-Loop Rewriting for Creative Image Captioning. - Vishakh Padmakumar; He He 001 (NAACL-HLT, 2022)

Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. - Vishakh Padmakumar; Leonard Lausen; Miguel Ballesteros; Sheng Zha; He He 001; George Karypis (NAACL-HLT, 2022)

QuALITY: Question Answering with Long Input Texts, Yes! - Richard Yuanzhe Pang; Alicia Parrish; Nitish Joshi; Nikita Nangia; Jason Phang; Angelica Chen; Vishakh Padmakumar; Johnny Ma; Jana Thompson; He He 001; Samuel R. Bowman (NAACL-HLT, 2022)

Two-Turn Debate Doesn't Help Humans Answer Hard Reading Comprehension Questions. - Alicia Parrish; Harsh Trivedi; Nikita Nangia; Vishakh Padmakumar; Jason Phang; Amanpreet Singh Saimbhi; Samuel R. Bowman (CoRR, 2022)

Reward Gaming in Conditional Text Generation. - Richard Yuanzhe Pang; Vishakh Padmakumar; Thibault Sellam; Ankur P. Parikh; He He 001 (ACL (1), 2023)

Extrapolative Controlled Sequence Generation via Iterative Refinement. - Vishakh Padmakumar; Richard Yuanzhe Pang; He He 001; Ankur P. Parikh (ICML, 2023)

Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD Examples. - Abulhair Saparov; Richard Yuanzhe Pang; Vishakh Padmakumar; Nitish Joshi; Mehran Kazemi; Najoung Kim; He He 001 (NeurIPS, 2023)

Investigating the Representation of Open Domain Dialogue Context for Transformer Models. - Vishakh Padmakumar; Behnam Hedayatnia; Di Jin; Patrick Lange; Seokhwan Kim; Nanyun Peng 001; Yang Liu 004; Dilek Hakkani-Tur (SIGDIAL, 2023)

Creativity Support in the Age of Large Language Models: An Empirical Study Involving Emerging Writers. - Tuhin Chakrabarty; Vishakh Padmakumar; Faeze Brahman; Smaranda Muresan (CoRR, 2023)

Debate Helps Supervise Unreliable Experts. - Julian Michael; Salsabila Mahdi; David Rein; Jackson Petty; Julien Dirani; Vishakh Padmakumar; Samuel R. Bowman (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Creativity Support in the Age of Large Language Models: An Empirical Study Involving Professional Writers. - Tuhin Chakrabarty; Vishakh Padmakumar; Faeze Brahman; Smaranda Muresan (Creativity & Cognition, 2024)

Does Writing with Language Models Reduce Content Diversity? - Vishakh Padmakumar; He He 001 (ICLR, 2024)

Beyond the Binary: Capturing Diverse Preferences With Reward Regularization. - Vishakh Padmakumar; Chuanyang Jin; Hannah Rose Kirk; He He 001 (CoRR, 2024)

Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs. - Angelica Chen; Jason Phang; Alicia Parrish; Vishakh Padmakumar; Chen Zhao; Samuel R. Bowman; Kyunghyun Cho (Trans. Mach. Learn. Res., 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)

Principled Content Selection to Generate Diverse and Personalized Multi-Document Summaries. - Vishakh Padmakumar; Zichao Wang 001; David Arbour; Jennifer Healey (ACL (1), 2025)

Transformers Struggle to Learn to Search. - Abulhair Saparov; Srushti Ajay Pawar; Shreyas Pimpalgaonkar; Nitish Joshi; Richard Yuanzhe Pang; Vishakh Padmakumar; Mehran Kazemi; Najoung Kim; He He 001 (ICLR, 2025)

Modifying Large Language Model Post-Training for Diverse Creative Writing. - John Joon Young Chung; Vishakh Padmakumar; Melissa Roemmele; Yuqian Sun; Max Kreminski (CoRR, 2025)

Beyond Memorization: Mapping the Originality-Quality Frontier of Language Models. - Vishakh Padmakumar; Chen Yueh-Han; Jane Pan; Valerie Chen; He He 001 (CoRR, 2025)

Evaluating the Diversity and Quality of LLM Generated Content. - Alexander Shypula; Shuo Li; Botong Zhang; Vishakh Padmakumar; Kayo Yin; Osbert Bastani (CoRR, 2025)

Setting The Table with Intent: Intent-aware Schema Generation and Editing for Literature Review Tables. - Vishakh Padmakumar; Joseph Chee Chang; Kyle Lo; Doug Downey; Aakanksha Naik (CoRR, 2025)