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20242026
most citedArtificial Intelligence for Food Innovation

3 citations · 3 across the 7 of their papers we have counts for

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16 papers · 1 filter

cs.CL2026

string2string Studio: An Interactive, In-Browser Platform for String-to-String Algorithms

Mirac Suzgun, James Zou, Stuart M. Shieber +1

We present string2string Studio, an interactive in-browser platform for string-to-string analysis across natural language processing, computational biology, and the digital humanit…

cs.CL2026

Evaluating Commercial AI Chatbots as News Intermediaries

Mirac Suzgun, Emily Shen, Federico Bianchi +5

AI chatbots are rapidly shaping how people encounter the news, yet no prior study has systematically measured how accurately these systems, with their proprietary search integratio…

cs.CL20261 cited

Verbalizing LLMs' assumptions to explain and control sycophancy

Myra Cheng, Isabel Sieh, Humishka Zope +7

LLMs can be socially sycophantic, affirming users when they ask questions like "am I in the wrong?" rather than providing genuine assessment. We hypothesize that this behavior aris…

cs.CL2026

Beyond Tokens: Concept-Level Training Objectives for LLMs

Laya Iyer, Pranav Somani, Alice Guo +2

The next-token prediction (NTP) objective has been foundational in the development of modern large language models (LLMs), driving advances in fluency and generalization. However,…

cs.CL2026

Accommodation and Epistemic Vigilance: A Pragmatic Account of Why LLMs Fail to Challenge Harmful Beliefs

Myra Cheng, Robert D. Hawkins, Dan Jurafsky

Large language models (LLMs) frequently fail to challenge users' harmful beliefs in domains ranging from medical advice to social reasoning. We argue that these failures can be und…

cs.CL2025

Generation Space Size: Understanding and Calibrating Open-Endedness of LLM Generations

Sunny Yu, Ahmad Jabbar, Robert Hawkins +2

Different open-ended generation tasks require different degrees of output diversity. However, current LLMs are often miscalibrated. They collapse to overly homogeneous outputs for…