10 papers
The LLM Fallacy: Misattribution in AI-Assisted Cognitive Workflows
Hyunwoo Kim, Harin Yu, Hanau Yi
The rapid integration of large language models (LLMs) into everyday workflows has transformed how individuals perform cognitive tasks such as writing, programming, analysis, and mu…
GoodPoint: Learning Constructive Scientific Paper Feedback from Author Responses
Jimin Mun, Chani Jung, Xuhui Zhou +2
While LLMs hold significant potential to transform scientific research, we advocate for their use to augment and empower researchers rather than to automate research without human…
SimpleToM: Exposing the Gap between Explicit ToM Inference and Implicit ToM Application in LLMs
Yuling Gu, Oyvind Tafjord, Hyunwoo Kim +4
Large language models (LLMs) are increasingly tested for a "Theory of Mind" (ToM) - the ability to attribute mental states to oneself and others. Yet most evaluations stop at expli…
HAICOSYSTEM: An Ecosystem for Sandboxing Safety Risks in Human-AI Interactions
Xuhui Zhou, Hyunwoo Kim, Faeze Brahman +9
AI agents are increasingly autonomous in their interactions with human users and tools, leading to increased interactional safety risks. We present HAICOSYSTEM, a framework examini…
Hypothesis-Driven Theory-of-Mind Reasoning for Large Language Models
Hyunwoo Kim, Melanie Sclar, Tan Zhi-Xuan +5
Existing LLM reasoning methods have shown impressive capabilities across various tasks, such as solving math and coding problems. However, applying these methods to scenarios witho…
Socratic-MCTS: Test-Time Visual Reasoning by Asking the Right Questions
David Acuna, Ximing Lu, Jaehun Jung +4
Recent research in vision-language models (VLMs) has centered around the possibility of equipping them with implicit long-form chain-of-thought reasoning -- akin to the success obs…