activity
20242026
most citedA Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomy

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2026

When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation

Henry Peng Zou, Chunyu Miao, Wei-Chieh Huang +16

As LLM agents transition from short, static problem solving to executing complex, long-horizon tasks in dynamic environments, the ability to handle user interruptions, such as addi…

cs.CL2025

RECODE-H: A Benchmark for Research Code Development with Interactive Human Feedback

Chunyu Miao, Henry Peng Zou, Yangning Li +28

Large language models (LLMs) show the promise in supporting scientific research implementation, yet their ability to generate correct and executable code remains limited. Existing…

cs.AI20251 cited

A Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomy

Henry Peng Zou, Wei-Chieh Huang, Yaozu Wu +10

Recent improvements in large language models (LLMs) have led many researchers to focus on building fully autonomous AI agents. This position paper questions whether this approach i…

cs.CL2025

TestNUC: Enhancing Test-Time Computing Approaches and Scaling through Neighboring Unlabeled Data Consistency

Henry Peng Zou, Zhengyao Gu, Yue Zhou +7

Test-time computing approaches, which leverage additional computational resources during inference, have been proven effective in enhancing large language model performance. This w…

cs.CL2024

Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges

Vinay Samuel, Yue Zhou, Henry Peng Zou

As large language models achieve increasingly impressive results, questions arise about whether such performance is from generalizability or mere data memorization. Thus, numerous…