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Home/Authors/Zhenyu Wu

Zhenyu Wu

4 indexed papers

Recent (6 mo)
4
With code
0
Influential cites
0
Benchmarked
0

Publications per year

4
26

Top categories

AI×2NLP×2Robotics×2Databases×1Info Retrieval×1HCI×1Vision×1ML×1

Frequent co-authors

Hira Beril Kucuk1×
Norman W Paton1×
Jiaoyan Chen1×
Yikun Fu1×
Bowen Fu1×
Shuang Cheng1×

Research Timeline

2026
UniIntervene: Agentic Intervention for Efficient Real-World Reinforcement Learning

UniIntervene proposes an agentic intervention model for human-in-the-loop reinforcement learning to reduce human interventions and improve policy efficiency.

R2RDreamer: 3D-aware Data Augmentation for Spatially-generalized 2D Manipulation Policies

The paper proposes a real-to-real demonstration augmentation framework, R2RDreamer, to improve spatial generalization in imitation-learned manipulation policies.

MacAgentBench: Benchmarking AI Agents on Real-World macOS Desktop

The paper presents MacAgentBench, a comprehensive macOS agent benchmark for evaluating computer use agents.

Single and Multi Truth Data Fusion using Large Language Models

This paper explores the use of Large Language Models (LLMs) in data fusion tasks for tabular data and shows their superiority over traditional methods.

Highlighted terms show continued research focus across papers

Papers

cs.DBcs.AIcs.CLEmpiricalRecentJun 26, 2026

Single and Multi Truth Data Fusion using Large Language Models

Hira Beril Kucuk, Norman W Paton, Jiaoyan Chen, Zhenyu Wu

This paper explores the use of Large Language Models (LLMs) in data fusion tasks for tabular data and shows their superiority over traditional methods.

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cs.AIcs.CLcs.HCEmpirical
Recent
Jun 21, 2026

MacAgentBench: Benchmarking AI Agents on Real-World macOS Desktop

Yikun Fu, Bowen Fu, Zhenyu Wu, Shuang Cheng +9 more

The paper presents MacAgentBench, a comprehensive macOS agent benchmark for evaluating computer use agents.

View →
cs.ROcs.CVEmpiricalRecentJun 15, 2026

R2RDreamer: 3D-aware Data Augmentation for Spatially-generalized 2D Manipulation Policies

Xiuwei Xu, Haowen Sun, Angyuan Ma, Yiwei Zhang +6 more

The paper proposes a real-to-real demonstration augmentation framework, R2RDreamer, to improve spatial generalization in imitation-learned manipulation policies.

View →
cs.ROcs.LGEmpiricalRecentJun 10, 2026

UniIntervene: Agentic Intervention for Efficient Real-World Reinforcement Learning

Haoyuan Deng, Yitong Gao, Yudong Lin, Haichao Liu +2 more

UniIntervene proposes an agentic intervention model for human-in-the-loop reinforcement learning to reduce human interventions and improve policy efficiency.

View →