Publications (7)
Talk is Cheap, Communication is Hard: Dynamic Grounding Failures and Repair in Multi-Agent Negotiation
Yiheng Yao, Chelsea Zou, Robert D. Hawkins
Grounding is the collaborative process of establishing mutual belief sufficient for a communicative goal. While static grounding maps language to a shared context, dynamic groundin…
A Unified Definition of Hallucination: It's The World Model, Stupid!
Emmy Liu, Varun Gangal, Chelsea Zou +7
Despite numerous attempts at mitigation since the inception of language models, hallucinations remain a persistent problem even in today's frontier LLMs. Why is this? We review exi…
Abstracted Gaussian Prototypes for True One-Shot Concept Learning
Chelsea Zou, Kenneth J. Kurtz
We introduce a cluster-based generative image segmentation framework to encode higher-level representations of visual concepts based on one-shot learning inspired by the Omniglot C…
ARDIE: AR, Dialogue, and Eye Gaze Policies for Human-Robot Collaboration
Chelsea Zou, Kishan Chandan, Yan Ding +1
Human-robot collaboration (HRC) has become increasingly relevant in industrial, household, and commercial settings. However, the effectiveness of such collaborations is highly depe…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1144
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
CalBench: Evaluating Coordination-Privacy Trade-offs in Multi-Agent LLMs
Chelsea Zou, Yiheng Yao, Selena She +2
Personal AI assistants are beginning to act as delegates with access to calendars, inboxes, and user preferences. Calendar scheduling makes the trust problem concrete: an assistant…
Thinking, Faithful and Stable: Mitigating Hallucinations in LLMs
Chelsea Zou, Yiheng Yao, Basant Khalil
This project develops a self correcting framework for large language models (LLMs) that detects and mitigates hallucinations during multi-step reasoning. Rather than relying solely…