activity
20152026
most citedWhen Are Tree Structures Necessary for Deep Learning of Representations?

131 citations · 319 across the 29 of their papers we have counts for

collaborators
Showing 2026 · cs.CLShow all

5 papers · 2 filters

cs.CL2026

Turning Speech Language Models into Multilingual Listeners

Tolúlopé Ògúnrèmí, Dan Jurafsky, Chris Manning +2

Speech Language Models (SLMs) that understand spoken language questions support only a few high-resource languages, limiting access to millions of people worldwide. This gap stems…

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★ 1 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…