3 papers
cs.HC2026
From Observation to Intervention: Identifiability of Latent User Bias in Human-AI Interaction
Lucas Biechy, Yuxiao Li, Zhonghao He +1
Alignment methods typically treat user behavior as a reliable proxy for underlying preferences. However, this assumption breaks down when users hold belief-dependent cognitive bias…
cs.CR2026
PrivacySkills: How Privacy Guidance Shapes Source Selection in LLM Agents
Lucas Biechy, Cédric Eichler, Héber H. Arcolezi +1
While prior work has documented privacy failures in LLM agents, it remains unclear how the presentation of privacy guidance influences their choice of information sources. We intro…
cs.AI2026
Jailbreaks for Black-Box Uncertainty Quantification in Large Reasoning Models
Lucas Biechy, Cédric Eichler, Adrien Boiret +1
While Large Reasoning Models (LRMs) excel at complex reasoning, alignment through reinforcement learning often induces systemic overconfidence. In production environments, where lo…