5 papers
KnowSim: Evaluating Information Calibration in LLM Assistants with User Simulators that Learn
Yoonjoo Lee, Hyoungwook Jin, Tae Soo Kim +3
To effectively collaborate with users on knowledge-intensive tasks, Large Language Models (LLMs) must perform information calibration: matching content to a user's evolving underst…
Agents Don't Just Agree, They Remember: Benchmarking Persistent Sycophancy in Stateful Personal Agents
Xutao Mao, Liangjie Zhao, Leyao Wang +6
Stateful personal agents increasingly maintain long-term user profiles, episodic memories, and reusable skills. This persistence turns conversational sycophancy into a state-writin…
CoPersona: Collaborative Persona Graphs for Robust LLM Personalization
Yangtian Zhang, Leyao Wang, Hiren Madhu +3
Real-world LLM personalization is often constrained by sparse and skewed user histories: most users provide only a handful of interactions, while even frequent users' logs capture…
SRTJ: Self-Evolving Rule-Driven Training-Free LLM Jailbreaking
Jindong Li, Ying Liu, Yali Fu +4
LLMs are increasingly equipped with safety alignment mechanisms, yet recent studies demonstrate that they remain vulnerable to jailbreaking attacks that elicit harmful behaviors wi…
Sensor2Text: Enabling Natural Language Interactions for Daily Activity Tracking Using Wearable Sensors
Wenqiang Chen, Jiaxuan Cheng, Leyao Wang +2
Visual Question-Answering, a technology that generates textual responses from an image and natural language question, has progressed significantly. Notably, it can aid in tracking…