Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? - Sewon Min; Xinxi Lyu; Ari Holtzman; Mikel Artetxe; Mike Lewis; Hannaneh Hajishirzi; Luke Zettlemoyer (EMNLP, 2022)

Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts. - Daniel Khashabi; Xinxi Lyu; Sewon Min; Lianhui Qin; Kyle Richardson 001; Sean Welleck; Hannaneh Hajishirzi; Tushar Khot; Ashish Sabharwal; Sameer Singh 001; Yejin Choi 001 (NAACL-HLT, 2022)

Z-ICL: Zero-Shot In-Context Learning with Pseudo-Demonstrations. - Xinxi Lyu; Sewon Min; Iz Beltagy; Luke Zettlemoyer; Hannaneh Hajishirzi (ACL (1), 2023)

FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. - Sewon Min; Kalpesh Krishna; Xinxi Lyu; Mike Lewis; Wen-tau Yih; Pang Wei Koh; Mohit Iyyer; Luke Zettlemoyer; Hannaneh Hajishirzi (EMNLP, 2023)

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. - Luca Soldaini; Rodney Kinney; Akshita Bhagia; Dustin Schwenk; David Atkinson; Russell Authur; Ben Bogin; Khyathi Raghavi Chandu; Jennifer Dumas; Yanai Elazar; Valentin Hofmann; Ananya Harsh Jha; et al. (ACL (1), 2024)

HREF: Human Response-Guided Evaluation of Instruction Following in Language Models. - Xinxi Lyu; Yizhong Wang; Hannaneh Hajishirzi; Pradeep Dasigi (CoRR, 2024)

Frustratingly Simple Retrieval Improves Challenging, Reasoning-Intensive Benchmarks. - Xinxi Lyu; Michael Duan; Rulin Shao; Pang Wei Koh; Sewon Min (CoRR, 2025)