activity
20242026
collaborators

6 papers

cs.CY2026

Safety Degradation in AI Agents

Cheng Yu, Benedikt Stroebl, Diyi Yang +1

Despite the growing integration of retrieval-enabled AI agents into society, their safety and ethical behavior remain inadequately understood. In particular, the integration of LLM…

cs.CL2025

ReplicationBench: Can AI Agents Replicate Astrophysics Research Papers?

Christine Ye, Sihan Yuan, Suchetha Cooray +10

Frontier AI agents show increasing promise as scientific research assistants, and may eventually be useful for extended, open-ended research workflows. However, in order to use age…

cs.AI2025

OpenCUA: Open Foundations for Computer-Use Agents

Xinyuan Wang, Bowen Wang, Dunjie Lu +39

Vision-language models have demonstrated impressive capabilities as computer-use agents (CUAs) capable of automating diverse computer tasks. As their commercial potential grows, cr…

cs.CL2025

When Large Language Models are Reliable for Judging Empathic Communication

Aakriti Kumar, Nalin Poungpeth, Diyi Yang +3

Large language models (LLMs) excel at generating empathic responses in text-based conversations. But, how reliably do they judge the nuances of empathic communication? We investiga…

cs.CL2025

PrivacyLens: Evaluating Privacy Norm Awareness of Language Models in Action

Yijia Shao, Tianshi Li, Weiyan Shi +2

As language models (LMs) are widely utilized in personalized communication scenarios (e.g., sending emails, writing social media posts) and endowed with a certain level of agency,…

cs.CL2024

Are Large Language Models Consistent over Value-laden Questions?

Jared Moore, Tanvi Deshpande, Diyi Yang

Large language models (LLMs) appear to bias their survey answers toward certain values. Nonetheless, some argue that LLMs are too inconsistent to simulate particular values. Are th…