Aryaman Arora, Dan Jurafsky, Christopher Potts, Noah D. Goodman. 2025. Bayesian scaling laws for in-context learning. ArXiv preprint.

Camp. N. P., Voigt, R., Hamedani, M. G., Jurafsky, D., Eberhardt, J. L. (2024). Leveraging body-worn camera footage to assess the effects of training on officer communication during traffic stops. PNAS Nexus 3 (9).

Cinoo Lee, Kristina Gligorić, Pratyusha Ria Kalluri, Maggie Harrington, Esin Durmus, Kiara L. Sanchez, Nay San, Danny Tse, Xuan Zhao, MarYam G. Hamedani, Hazel Rose Markus, Dan Jurafsky, Jennifer L. Eberhardt. 2024. People who share encounters with racism are silenced online by humans and machines, but a guideline-reframing intervention holds promise. Proceedings of the National Academy of Sciences 121:38.

Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, Sharese King. 2024. AI generates covertly racist decisions about people based on their dialect. Nature 2024.

Kristina Gligorić, Tijana Zrnic, Cinoo Lee, Emmanuel J. Candès, and Dan Jurafsky. 2024. Can Unconfident LLM Annotations Be Used for Confident Conclusions? ArXiv.

Heidi C. Zhang, Shabnam Behzad, Kawin Ethayarajh, Dan Jurafsky. 2024. Data Checklist: On Unit-Testing Datasets with Usable Information. COLM 2024.

Aryaman Arora, Dan Jurafsky, Christopher Potts. 2024. CausalGym: Benchmarking causal interpretability methods on linguistic tasks. Proceedings of ACL. Outstanding Paper Award, and Senior Area Chair Award.

Zhengxuan Wu*, Aryaman Arora*, Zheng Wang, Atticus Geiger, Dan Jurafsky, Christopher D. Manning, Christopher Potts. 2024. ReFT: Representation Finetuning for Language Models. NeurIPS. Spotlight.

Cole Simmons, Richard Diehl Martinez, and Dan Jurafsky. 2024. SumTablets: A Transliteration Dataset of Sumerian Tablets. ACL 2024 Workshop on Machine Learning for Ancient Languages.

Anton de la Fuente and Dan Jurafsky. 2024. A layer-wise analysis of Mandarin and English suprasegmentals in SSL speech models. Interspeech 2024.

Eva Portelance, Michael C. Frank, Dan Jurafsky. 2024. Learning the meanings of function words from grounded language using a visual question answering model. Cognitive Science 48:5.

Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, and Douwe Kiela. 2024. KTO: Model Alignment as Prospect Theoretic Optimization. Proceedings of ICML 2024.

Federico Bianchi, Patrick John Chia, Mert Yuksekgonul, Jacopo Tagliabue, Dan Jurafsky, James Zou. 2024. How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis Proceedings of ICML 2024.

Kristina Gligoric, Myra Cheng, Lucia Zheng, Esin Durmus, Dan Jurafsky. 2024. NLP Systems That Can't Tell Use from Mention Censor Counterspeech, but Teaching the Distinction Helps. Proceedings of NAACL 2024.

Omar Shaikh*, Kristina Gligorić*, Ashna Khetan, Matthias Gerstgrasser, Diyi Yang, Dan Jurafsky. 2024. Grounding Gaps in Language Model Generations. Proceedings of NAACL 2024.

Myra Cheng, Kristina Gligoric, Tiziano Piccardi, Dan Jurafsky. 2024. AnthroScore: A Computational Linguistic Measure of Anthropomorphism. Proceedings of EACL 2024

Yiwei Luo, Kristina Gligorić, Dan Jurafsky. 2024. Othering and low prestige framing of immigrant cuisines in US restaurant reviews and large language models. Proceedings of ICWSM 2024.

Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, Paul Röttger, Dan Jurafsky, Tatsunori Hashimoto, James Zou. 2024. Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions. Proceedings of ICLR 2024.

Nay San, Georgios Paraskevopoulos, Aryaman Arora, Xiluo He, Prabhjot Kaur, Oliver Adams, Dan Jurafsky. 2024. Predicting positive transfer for improved low-resource speech recognition using acoustic pseudo-tokens.. Proceedings of SIGTYP 2024.

Garrett Tanzer, Mirac Suzgun, Eline Visser, Dan Jurafsky, Luke Melas-Kyriazi. 2024. A Benchmark for Learning to Translate a New Language from One Grammar Book. Proceedings of ICLR 2024.

Travis Zack, Eric Lehman, Mirac Suzgun, Jorge A Rodriguez, Leo Anthony Celi, Judy Gichoya, Dan Jurafsky, Peter Szolovits, David W Bates, Raja-Elie E Abdulnour, Atul Butte, Emily Alsentzer. 2024. Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study. The Lancet Digital Health, 6:1, e12-e22.