activity
20242026
most citedBootstrapping Cognitive Agents with a Large Language Model

5 citations · 5 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG2026

Selection-Based Structured Reasoning: Toward Efficient Multimodal Search Agents

Feiyu Gavin Zhu, Xiaoyu Zhu, Jiqi Yang +9

Multimodal agents commonly generate free-form reasoning before each action. For small models, limited model capacity can result in lengthy reasoning that provides little useful gui…

cs.LG2026

Iterative Policy Refinement through Semantic Rollout Analysis

Feiyu Gavin Zhu, Qi Xu, Zhifei Deng +4

Structured policies improve efficiency, robustness, and interpretability in imitation learning by introducing task-specific inductive bias, but existing structure generation method…

cs.HC2026

What Do You Think I Think? Accounting for Human Beliefs Using Second-Order Theory of Mind

Patrick Callaghan, Reid Simmons, Henny Admoni

Discrepancies between an agent's actual knowledge and what a person thinks the agent knows can hinder interactions. If an agent could detect such discrepancies, it could provide fe…

cs.AI2026

InterPReT: Interactive Policy Restructuring and Training Enable Effective Imitation Learning from Laypersons

Feiyu Gavin Zhu, Jean Oh, Reid Simmons

Imitation learning has shown success in many tasks by learning from expert demonstrations. However, most existing work relies on large-scale demonstrations from technical professio…

cs.AI2025

Sample-Efficient Behavior Cloning Using General Domain Knowledge

Feiyu Zhu, Jean Oh, Reid Simmons

Behavior cloning has shown success in many sequential decision-making tasks by learning from expert demonstrations, yet they can be very sample inefficient and fail to generalize t…

cs.AI2024★ 5 cited

Bootstrapping Cognitive Agents with a Large Language Model

Feiyu Zhu, Reid Simmons

Large language models contain noisy general knowledge of the world, yet are hard to train or fine-tune. On the other hand cognitive architectures have excellent interpretability an…