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Home/Authors/Pengkun Wang

Pengkun Wang

3 indexed papers

Recent (6 mo)
3
With code
0
Influential cites
0
Benchmarked
0

Publications per year

3
26

Top categories

AI×2Vision×1ML×1

Frequent co-authors

Xucong Wang2×
Weijia Cao1×
Ning Wang1×
Xiaofei Yang1×
Ziyu Ma1×
Yong Wang1×

Research Timeline

2026
FedMPT: Federated Multi-label Prompt Tuning of Vision-Language Models

FedMPT introduces a novel federated learning framework for Multi-Label Recognition (MLR) using Vision-Language Models (VLMs) by leveraging generalizable conditions to mitigate label overfitting and improve robustness.

APPO: Agentic Procedural Policy Optimization

This paper proposes a new method for agentic Reinforcement Learning called Agentic Procedural Policy Optimization (APPO) that improves tool-use capabilities by assigning credit to fine-grained decision points.

DAPGNet: Dynamic Adaptive Physics-Guided Graph Diffusion Network for Hyperspectral Image Classification

This paper proposes DAPGNet, a dynamic adaptive physics-guided graph diffusion network for hyperspectral image classification, which achieves state-of-the-art performance on four datasets.

Highlighted terms show continued research focus across papers

Papers

cs.CVEmpiricalRecentJul 16, 2026

DAPGNet: Dynamic Adaptive Physics-Guided Graph Diffusion Network for Hyperspectral Image Classification

Pengkun Wang, Weijia Cao, Ning Wang, Xiaofei Yang

This paper proposes DAPGNet, a dynamic adaptive physics-guided graph diffusion network for hyperspectral image classification, which achieves state-of-the-art performance on four datasets.

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cs.LGcs.AIEmpirical
Recent
Jun 10, 2026

APPO: Agentic Procedural Policy Optimization

Xucong Wang, Ziyu Ma, Yong Wang, Yuxiang Ji +4 more

This paper proposes a new method for agentic Reinforcement Learning called Agentic Procedural Policy Optimization (APPO) that improves tool-use capabilities by assigning credit to fine-grained decisio…

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cs.AIRecentMay 27, 2026

FedMPT: Federated Multi-label Prompt Tuning of Vision-Language Models

Xucong Wang, Pengkun Wang, Zhe Zhao, Liheng Yu +2 more

FedMPT introduces a novel federated learning framework for Multi-Label Recognition (MLR) using Vision-Language Models (VLMs) by leveraging generalizable conditions to mitigate label overfitting and im…

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