Preprints

Andrew Lanpouthakoun*, Aryaman Arora*, Zhengxuan Wu, Dhruv Pai, Ben Keigwin, Dan Jurafsky, Christopher Potts. 2026. PreFT: Prefill-only finetuning for inference efficiency. arXiv:2605.14217.

Myra Cheng, Isabel Sieh, Humishka Zope, Sunny Yu, Lujain Ibrahim, Aryaman Arora, Jared Moore, Desmond Ong, Dan Jurafsky, Diyi Yang. 2026 Verbalizing LLMs' assumptions to explain and control sycophancy. ArXiv.

Christine Zhang, Dan Jurafsky, Chen Shani. 2026. Learning Concepts, Not Tokens: Self-Supervised Semantic Alignment for Language Models. ArXiv pre-print under review.

Sunny Yu, Myra Cheng, Ahmad Jabbar, Ilia Sucholutsky, Katherine M. Collins, Dan Jurafsky, Robert D. Hawkins. 2026. The Efficiency-Gain Illusion: People Underestimate the Rate of AI Use and Overestimate Its Benefits on Simple Tasks. ArXiv pre-print under review.

Sunny Yu, Ahmad Jabbar, Robert Hawkins, Dan Jurafsky, Myra Cheng. 2025. Generation Space Size: Understanding and Calibrating Open-Endedness of LLM Generations. ArXiv pre-print, under review.

Myra Cheng, Isabel Sieh, Humishka Zope, Sunny Yu, Lujain Ibrahim, Aryaman Arora, Jared Moore, Desmond Ong, Dan Jurafsky, Diyi Yang. 2026. Verbalizing LLMs' assumptions to explain and control sycophancy arXiv:2604.03058

2026

Myra Cheng, Cinoo Lee, Pranav Khadpe, Sunny Yu, Dyllan Han, Dan Jurafsky. Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence. , Science, Vol. 391, No. 6792.
Press: NY Times, AP, Scientific American.

Rishi Bommasani, Sarah H. Bana, Kathleen A. Creel, Dan Jurafsky Percy Liang. 2026. Algorithmic Monocultures in Hiring. FAccT ’26, Montreal, QC, Canada

Anna Thomas, Georgios Zaverdinos, Petros Mandalis, Andreas Orfanoudakis, Akihiro Takino, Sohum Patnaik, David J. Kraus, Panos Kostopoulos, Caroline Cotto, Nikos Tsiaparas, Dan Jurafsky, Aadit Patel. 2026. Expert-guided Bayesian optimization for sustainable protein design. ICML 2026 Workshop AI4Science.

Kaitlyn Zhou, Kristina Gligorić, Myra Cheng, Michelle S. Lam, Vyoma Raman, Boluwatife Amin, Caeley Woo, Michael Brockman, Hannah Cha, and Dan Jurafsky. Attention to Non-Adopters. Findings of ACL 2026.

Myra Cheng, Robert D. Hawkins, Dan Jurafsky. 2026. Accommodation and Epistemic Vigilance: A Pragmatic Account of Why LLMs Fail to Challenge Harmful Beliefs. To appear, ACL 2026. Press: IEEE Spectrum.

Bianca Datta, Markus J. Buehler, Yvonne Chow, Kristina Gligoric, Dan Jurafsky, David L. Kaplan, Rodrigo Ledesma-Amaro, Giorgia Del Missier, Lisa Neidhardt, Karim Pichara, Benjamin Sanchez-Lengeling, Miek Schlangen, Skyler R. St. Pierre, Ilias Tagkopoulos, Anna Thomas, Nicholas J. Watson, Ellen Kuhl. 2026. Artificial Intelligence for Food Innovation. Nature Food.

Isabel O. Gallegos, Chen Shani, Weiyan Shi, Federico Bianchi, Izzy Gainsburg, Dan Jurafsky, Robb Willer. 2026. Labeling messages as AI-generated does not reduce their persuasive effects. PNAS Nexus, Volume 5, Issue 2, February 2026, pgag008.

Moran Mizrahi, Chen Shani, Gabriel Stanovsky, Dan Jurafsky, Dafna Shahaf. 2026 Cooking Up Creativity: Enhancing LLM Creativity through Structured Recombination. TACL 2026.

Doumbouya, Moussa Koulako Bala, Dan Jurafsky, and Christopher D. Manning. 2026. Tversky Neural Networks: Psychologically Plausible Deep Learning with Differentiable Tversky Similarity. ICLR 2026

Myra Cheng*, Sunny Yu*, Cinoo Lee, Pranav Khadpe, Lujain Ibrahim, Dan Jurafsky. ELEPHANT: Measuring and Understanding Social Sycophancy in LLMs.. ICLR 2026. [code] Press coverage by MIT Technology Review and VentureBeat.

Chen Shani, Dan Jurafsky, Yann LeCun, Ravid Shwartz-Ziv. 2026. From Tokens to Thoughts: How LLMs and Humans Trade Compression for Meaning. ICLR 2026.

*Martijn Bartelds, *Nandi, Ananjan, Doumbouya, Moussa K. B., Jurafsky, Dan, Hashimoto, Tatsunori, and Karen Livescu (2026). CTC-DRO: Robust Optimization for Reducing Language Disparities in Speech Recognition. ICLR.

Mirac Suzgun, Mert Yuksekgonul, Federico Bianchi, Dan Jurafsky, James Zou. 2026. Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory. EACL 2026.

Laya Iyer; Pranav Somani; Alice Guo; Dan Jurafsky; Chen Shani. 2026. Beyond Tokens: Concept-Level Training Objectives for LLMs. EACL 2026