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20232026
most citedQuantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting

51 citations · 89 across the 20 of their papers we have counts for

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6 papers · 1 filter

cs.HC2026

Jarvis: A Proactive Speech Agent for Multi-Party Conversations

Seunghyun Oh, Hirotaka Hiraki, Shuyue Stella Li +2

Speech agents are reactive and dyadic: they speak when spoken to, and to one person at a time. We ask what it takes for a speech agent to instead take part in a conversation among…

cs.CL2026

Evaluating Large Language Models for Antisemitic Incident Classification

Karina Halevy, Julia Mendelsohn, Chan Young Park +2

Addressing hate and violence in society requires timely detection of hateful events from public reporting, but automated identification of hateful events remains underexplored. We…

cs.CL2026

Moral Safety in LLMs: Exposing Performative Compliance with Puzzled Cues

Mohammadamin Shafiei, Shuyue Stella Li, Yulia Tsvetkov

As large language models take on morally consequential roles in healthcare, legal, and hiring contexts, we need to examine whether their ethical behaviors are genuine or superficia…

cs.AI2026

Scaling Participation in Modular AI Systems

Shangbin Feng, Yike Wang, Weijia Shi +3

Humanity is a mosaic of multifaceted talents and needs, and any truly intelligent AI must reflect that richness. Yet the LLMs used by all are built by the few -- a centralized mark…

cs.CL2026

Privasis: Synthesizing the Largest "Public" Private Dataset from Scratch

Hyunwoo Kim, Niloofar Mireshghallah, Michael Duan +11

Research involving privacy-sensitive data has always been constrained by data scarcity, standing in sharp contrast to other areas that have benefited from data scaling. This challe…

cs.CL2026

MoCo: A One-Stop Shop for Model Collaboration Research

Shangbin Feng, Yuyang Bai, Ziyuan Yang +17

Advancing beyond single monolithic language models (LMs), recent research increasingly recognizes the importance of model collaboration, where multiple LMs collaborate, compose, an…