activity
20232026
most citedPersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits

32 citations · 35 across the 15 of their papers we have counts for

collaborators

15 papers

cs.AI2026

TeamBench: Evaluating Agent Coordination under Enforced Role Separation

Yubin Kim, Chanwoo Park, Taehan Kim +9

Agent systems often decompose a task across multiple roles, but these roles are typically specified by prompts rather than enforced by access controls. Without enforcement, a team…

cs.AI2026★ 2 cited

An AI Co-Data-Scientist for Prioritizing Candidate Biomarkers from Wearable Sensor Data

Yubin Kim, Salman Rahman, Samuel Schmidgall +33

Wearable devices generate continuous physiological and behavioral data, but converting these signals into clinically reviewable biomarker hypotheses remains labor-intensive. We int…

cs.CL2026

The Hidden Puppet Master: Predicting Human Belief Change in Manipulative LLM Dialogues

Jocelyn Shen, Amina Luvsanchultem, Jessica Kim +6

As users increasingly turn to LLMs for practical and personal advice, they become vulnerable to subtle steering toward hidden incentives misaligned with their own interests. While…

cs.RO2026

A Modern System Recipe for Situated Embodied Human-Robot Conversation with Real-Time Multimodal LLMs and Tool-Calling

Dong Won Lee, Sarah Gillet, Louis-Philippe Morency +2

Situated embodied conversation requires robots to interleave real-time dialogue with active perception: deciding what to look at, when to look, and what to say under tight latency…

cs.AI2026

Collaborative Multi-Agent Test-Time Reinforcement Learning for Reasoning

Zhiyuan Hu, Yunhai Hu, Juncheng Liu +9

Multi-agent systems have evolved into practical LLM-driven collaborators for many applications, gaining robustness from diversity and cross-checking. However, multi-agent RL (MARL)…

cs.LG2026

Rewarding the Rare: Uniqueness-Aware RL for Creative Problem Solving in LLMs

Zhiyuan Hu, Yucheng Wang, Yufei He +7

Reinforcement learning (RL) has become a central paradigm for post-training large language models (LLMs), particularly for complex reasoning tasks, yet it often suffers from explor…