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cs.CL2025
Language Models can Subtly Deceive Without Lying: A Case Study on Strategic Phrasing in Legislation
Atharvan Dogra, Krishna Pillutla, Ameet Deshpande +5
We explore the ability of large language models (LLMs) to engage in subtle deception through strategically phrasing and intentionally manipulating information. This harmful behavio…
cs.CL2025
PersonaGym: Evaluating Persona Agents and LLMs
Vinay Samuel, Henry Peng Zou, Yue Zhou +6
Persona agents, which are LLM agents conditioned to act according to an assigned persona, enable contextually rich and user aligned interactions across domains like education and h…
cs.CL2025
Probing AI Safety with Source Code
Ujwal Narayan, Shreyas Chaudhari, Ashwin Kalyan +4
Large language models (LLMs) have become ubiquitous, interfacing with humans in numerous safety-critical applications. This necessitates improving capabilities, but importantly cou…