5 papers
Social-R1: Towards Human-like Social Reasoning in LLMs
Jincenzi Wu, Yuxuan Lei, Jianxun Lian +5
While large language models demonstrate remarkable capabilities across numerous domains, social intelligence - the capacity to perceive social cues, infer mental states, and genera…
Visuospatial Perspective Taking in Multimodal Language Models
Jonathan Prunty, Seraphina Zhang, Patrick Quinn +3
As multimodal language models (MLMs) are increasingly used in social and collaborative settings, it is crucial to evaluate their perspective-taking abilities. Existing benchmarks l…
Contextualized Privacy Defense for LLM Agents
Yule Wen, Yanzhe Zhang, Jianxun Lian +3
LLM agents increasingly act on users' personal information, yet existing privacy defenses remain limited in both design and adaptability. Most prior approaches rely on static or pa…
Learning to summarize user information for personalized reinforcement learning from human feedback
Hyunji Nam, Yanming Wan, Mickel Liu +3
As everyday use cases of large language model (LLM) AI assistants have expanded, it is becoming increasingly important to personalize responses to align to different users' prefere…
Personalized Safety in LLMs: A Benchmark and A Planning-Based Agent Approach
Yuchen Wu, Edward Sun, Kaijie Zhu +4
Large language models (LLMs) typically generate identical or similar responses for all users given the same prompt, posing serious safety risks in high-stakes applications where us…