Effective Forum Curation via Multi-task Learning. - Faeze Brahman; Nikhil Varghese; Suma Bhat; Snigdha Chaturvedi (EDM, 2020)

Modeling Protagonist Emotions for Emotion-Aware Storytelling. - Faeze Brahman; Snigdha Chaturvedi (EMNLP (1), 2020)

Cue Me In: Content-Inducing Approaches to Interactive Story Generation. - Faeze Brahman; Alexandru Petrusca; Snigdha Chaturvedi (AACL/IJCNLP, 2020)

Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision. - Faeze Brahman; Vered Shwartz; Rachel Rudinger; Yejin Choi 001 (AAAI, 2021)

"Let Your Characters Tell Their Story": A Dataset for Character-Centric Narrative Understanding. - Faeze Brahman; Meng Huang; Oyvind Tafjord; Chao Zhao 002; Mrinmaya Sachan; Snigdha Chaturvedi (EMNLP (Findings), 2021)

Is Everything in Order? A Simple Way to Order Sentences. - Somnath Basu Roy Chowdhury; Faeze Brahman; Snigdha Chaturvedi (EMNLP (1), 2021)

Uncovering Implicit Gender Bias in Narratives through Commonsense Inference. - Tenghao Huang; Faeze Brahman; Vered Shwartz; Snigdha Chaturvedi (EMNLP (Findings), 2021)

Reformulating Sentence Ordering as Conditional Text Generation. - Somnath Basu Roy Chowdhury; Faeze Brahman; Snigdha Chaturvedi (CoRR, 2021)

ParsiNLU: A Suite of Language Understanding Challenges for Persian. - Daniel Khashabi; Arman Cohan; Siamak Shakeri; Pedram Hosseini; Pouya Pezeshkpour; Malihe Alikhani; Moin Aminnaseri; Marzieh Bitaab; Faeze Brahman; Sarik Ghazarian; Mozhdeh Gheini; Arman Kabiri; et al. (Trans. Assoc. Comput. Linguistics, 2021)

Grounded Keys-to-Text Generation: Towards Factual Open-Ended Generation. - Faeze Brahman; Baolin Peng; Michel Galley; Sudha Rao; Bill Dolan; Snigdha Chaturvedi; Jianfeng Gao 001 (EMNLP (Findings), 2022)

Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations. - Jaehun Jung; Lianhui Qin; Sean Welleck; Faeze Brahman; Chandra Bhagavatula; Ronan Le Bras 001; Yejin Choi 001 (EMNLP, 2022)

Towards Inter-character Relationship-driven Story Generation. - Anvesh Rao Vijjini; Faeze Brahman; Snigdha Chaturvedi (EMNLP, 2022)

NarraSum: A Large-Scale Dataset for Abstractive Narrative Summarization. - Chao Zhao 002; Faeze Brahman; Kaiqiang Song; Wenlin Yao; Dian Yu 001; Snigdha Chaturvedi (EMNLP (Findings), 2022)

Revisiting Generative Commonsense Reasoning: A Pre-Ordering Approach. - Chao Zhao 002; Faeze Brahman; Tenghao Huang; Snigdha Chaturvedi (NAACL-HLT (Findings), 2022)

REV: Information-Theoretic Evaluation of Free-Text Rationales. - Hanjie Chen; Faeze Brahman; Xiang Ren 001; Yangfeng Ji; Yejin Choi 001; Swabha Swayamdipta (ACL (1), 2023)

STEER: Unified Style Transfer with Expert Reinforcement. - Skyler Hallinan; Faeze Brahman; Ximing Lu; Jaehun Jung; Sean Welleck; Yejin Choi 001 (EMNLP (Findings), 2023)

Affective and Dynamic Beam Search for Story Generation. - Tenghao Huang; Ehsan Qasemi; Bangzheng Li; He Wang; Faeze Brahman; Muhao Chen 001; Snigdha Chaturvedi (EMNLP (Findings), 2023)

Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. - Ximing Lu; Faeze Brahman; Peter West; Jaehun Jung; Khyathi Raghavi Chandu; Abhilasha Ravichander; Prithviraj Ammanabrolu; Liwei Jiang; Sahana Ramnath; Nouha Dziri; Jillian Fisher; Bill Y. Lin; et al. (EMNLP, 2023)

What Makes it Ok to Set a Fire? Iterative Self-distillation of Contexts and Rationales for Disambiguating Defeasible Social and Moral Situations. - Kavel Rao; Liwei Jiang; Valentina Pyatkin; Yuling Gu; Niket Tandon; Nouha Dziri; Faeze Brahman; Yejin Choi 001 (EMNLP (Findings), 2023)

Generating Sequences by Learning to Self-Correct. - Sean Welleck; Ximing Lu; Peter West; Faeze Brahman; Tianxiao Shen; Daniel Khashabi; Yejin Choi 001 (ICLR, 2023)

SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks. - Bill Yuchen Lin; Yicheng Fu; Karina Yang; Faeze Brahman; Shiyu Huang 001; Chandra Bhagavatula; Prithviraj Ammanabrolu; Yejin Choi 001; Xiang Ren 001 (NeurIPS, 2023)

Improving Language Models with Advantage-based Offline Policy Gradients. - Ashutosh Baheti; Ximing Lu; Faeze Brahman; Ronan Le Bras 001; Maarten Sap; Mark O. Riedl (CoRR, 2023)

Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing. - Jaehun Jung; Peter West; Liwei Jiang; Faeze Brahman; Ximing Lu; Jillian Fisher; Taylor Sorensen; Yejin Choi 001 (CoRR, 2023)

PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning. - Faeze Brahman; Chandra Bhagavatula; Valentina Pyatkin; Jena D. Hwang; Xiang Lorraine Li; Hirona Jacqueline Arai; Soumya Sanyal 001; Keisuke Sakaguchi; Xiang Ren 001; Yejin Choi 001 (CoRR, 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)

Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs. - Da Yin; Faeze Brahman; Abhilasha Ravichander; Khyathi Raghavi Chandu; Kai-Wei Chang; Yejin Choi 001; Bill Yuchen Lin (CoRR, 2023)

In Search of the Long-Tail: Systematic Generation of Long-Tail Knowledge via Logical Rule Guided Search. - Huihan Li 001; Yuting Ning; Zeyi Liao; Siyuan Wang; Xiang Lorraine Li; Ximing Lu; Faeze Brahman; Wenting Zhao; Yejin Choi 001; Xiang Ren 001 (CoRR, 2023)

One Size Does Not Fit All: Customizing Open-Domain Procedures. - Yash Kumar Lal; Li Zhang 039; Faeze Brahman; Bodhisattwa Prasad Majumder; Peter Clark; Niket Tandon (CoRR, 2023)

Tailoring with Targeted Precision: Edit-Based Agents for Open-Domain Procedure Customization. - Yash Kumar Lal; Li Zhang 039; Faeze Brahman; Bodhisattwa Prasad Majumder; Peter Clark; Niket Tandon (ACL (Findings), 2024)

Agent Lumos: Unified and Modular Training for Open-Source Language Agents. - Da Yin; Faeze Brahman; Abhilasha Ravichander; Khyathi Raghavi Chandu; Kai-Wei Chang; Yejin Choi 001; Bill Yuchen Lin (ACL (1), 2024)

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)

In Search of the Long-Tail: Systematic Generation of Long-Tail Inferential Knowledge via Logical Rule Guided Search. - Huihan Li 001; Yuting Ning; Zeyi Liao; Siyuan Wang; Xiang Li 069; Ximing Lu; Wenting Zhao; Faeze Brahman; Yejin Choi 001; Xiang Ren 001 (EMNLP, 2024)

How to Train Your Fact Verifier: Knowledge Transfer with Multimodal Open Models. - Jaeyoung Lee; Ximing Lu; Jack Hessel; Faeze Brahman; Youngjae Yu; Yonatan Bisk; Yejin Choi 001; Saadia Gabriel (EMNLP (Findings), 2024)

Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models. - Ashutosh Baheti; Ximing Lu; Faeze Brahman; Ronan Le Bras 001; Maarten Sap; Mark O. Riedl (ICLR, 2024)

PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning. - Faeze Brahman; Chandra Bhagavatula; Valentina Pyatkin; Jena D. Hwang; Xiang Lorraine Li; Hirona Jacqueline Arai; Soumya Sanyal 001; Keisuke Sakaguchi; Xiang Ren 001; Yejin Choi 001 (ICLR, 2024)

The Generative AI Paradox: "What It Can Create, It May Not Understand". - Peter West; Ximing Lu; Nouha Dziri; Faeze Brahman; Linjie Li; Jena D. Hwang; Liwei Jiang; Jillian Fisher; Abhilasha Ravichander; Khyathi Raghavi Chandu; Benjamin Newman; Pang Wei Koh; et al. (ICLR, 2024)

Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model. - Jaehun Jung; Peter West; Liwei Jiang; Faeze Brahman; Ximing Lu; Jillian Fisher; Taylor Sorensen; Yejin Choi 001 (NAACL-HLT, 2024)

MacGyver: Are Large Language Models Creative Problem Solvers? - Yufei Tian; Abhilasha Ravichander; Lianhui Qin; Ronan Le Bras 001; Raja Marjieh; Nanyun Peng 001; Yejin Choi 001; Thomas L. Griffiths 001; Faeze Brahman (NAACL-HLT, 2024)

UNcommonsense Reasoning: Abductive Reasoning about Uncommon Situations. - Wenting Zhao; Justin T. Chiu; Jena D. Hwang; Faeze Brahman; Jack Hessel; Sanjiban Choudhury; Yejin Choi 001; Xiang Li 069; Alane Suhr (NAACL-HLT, 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)

WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models. - Liwei Jiang; Kavel Rao; Seungju Han 002; Allyson Ettinger; Faeze Brahman; Sachin Kumar 009; Niloofar Mireshghallah; Ximing Lu; Maarten Sap; Yejin Choi 001; Nouha Dziri (NeurIPS, 2024)

Information-Theoretic Distillation for Reference-less Summarization. - Jaehun Jung; Ximing Lu; Liwei Jiang; Faeze Brahman; Peter West; Pang Wei Koh; Yejin Choi 001 (CoRR, 2024)

WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild. - Bill Yuchen Lin; Yuntian Deng; Khyathi Raghavi Chandu; Faeze Brahman; Abhilasha Ravichander; Valentina Pyatkin; Nouha Dziri; Ronan Le Bras 001; Yejin Choi 001 (CoRR, 2024)

HAICOSYSTEM: An Ecosystem for Sandboxing Safety Risks in Human-AI Interactions. - Xuhui Zhou; Hyunwoo Kim 002; Faeze Brahman; Liwei Jiang; Hao Zhu 011; Ximing Lu; Frank Xu; Bill Yuchen Lin; Yejin Choi 001; Niloofar Mireshghallah; Ronan Le Bras 001; Maarten Sap (CoRR, 2024)

RESTOR: Knowledge Recovery through Machine Unlearning. - Keivan Rezaei; Khyathi Raghavi Chandu; Soheil Feizi; Yejin Choi 001; Faeze Brahman; Abhilasha Ravichander (CoRR, 2024)

TÜLU 3: Pushing Frontiers in Open Language Model Post-Training. - Nathan Lambert 001; Jacob Morrison; Valentina Pyatkin; Shengyi Huang; Hamish Ivison; Faeze Brahman; Lester James V. Miranda; Alisa Liu; Nouha Dziri; Shane Lyu; Yuling Gu; Saumya Malik; et al. (CoRR, 2024)

Hybrid Preferences: Learning to Route Instances for Human vs. AI Feedback. - Lester James Validad Miranda; Yizhong Wang; Yanai Elazar; Sachin Kumar 009; Valentina Pyatkin; Faeze Brahman; Noah A. Smith; Hannaneh Hajishirzi; Pradeep Dasigi (ACL (1), 2025)

Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement. - Jaehun Jung; Faeze Brahman; Yejin Choi 001 (ICLR, 2025)

AI-LieDar : Examine the Trade-off Between Utility and Truthfulness in LLM Agents. - Zhe Su; Xuhui Zhou; Sanketh Rangreji; Anubha Kabra; Julia Mendelsohn; Faeze Brahman; Maarten Sap (NAACL (Long Papers), 2025)

Multi-Attribute Constraint Satisfaction via Language Model Rewriting. - Ashutosh Baheti; Debanjana Chakraborty; Faeze Brahman; Ronan Le Bras 001; Ximing Lu; Nouha Dziri; Yejin Choi 001; Mark O. Riedl; Maarten Sap (Trans. Mach. Learn. Res., 2025)

RESTOR: Knowledge Recovery in Machine Unlearning. - Keivan Rezaei; Khyathi Raghavi Chandu; Soheil Feizi; Yejin Choi 001; Faeze Brahman; Abhilasha Ravichander (Trans. Mach. Learn. Res., 2025)

2 OLMo 2 Furious. - Team OLMo; Pete Walsh; Luca Soldaini; Dirk Groeneveld; Kyle Lo; Shane Arora; Akshita Bhagia; Yuling Gu; Shengyi Huang; Matt Jordan; Nathan Lambert 001; Dustin Schwenk; et al. (CoRR, 2025)

IssueBench: Millions of Realistic Prompts for Measuring Issue Bias in LLM Writing Assistance. - Paul Röttger; Musashi Hinck; Valentin Hofmann; Kobi Hackenburg; Valentina Pyatkin; Faeze Brahman; Dirk Hovy (CoRR, 2025)

Aligning LLMs to Ask Good Questions A Case Study in Clinical Reasoning. - Shuyue Stella Li; Jimin Mun; Faeze Brahman; Jonathan Ilgen; Yulia Tsvetkov; Maarten Sap (CoRR, 2025)

Large-Scale Data Selection for Instruction Tuning. - Hamish Ivison; Muru Zhang; Faeze Brahman; Pang Wei Koh; Pradeep Dasigi (CoRR, 2025)

ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data. - Tong Chen; Faeze Brahman; Jiacheng Liu 010; Niloofar Mireshghallah; Weijia Shi; Pang Wei Koh; Luke Zettlemoyer; Hannaneh Hajishirzi (CoRR, 2025)

Let Them Down Easy! Contextual Effects of LLM Guardrails on User Perceptions and Preferences. - Mingqian Zheng; Wenjia Hu; Patrick Zhao; Motahhare Eslami; Jena D. Hwang; Faeze Brahman; Carolyn Rose; Maarten Sap (CoRR, 2025)