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Author

Pengwen Dai

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Entity-Dependent Relation Learning for Knowledge Graph Completion

Knowledge graph completion (KGC) aims to predict missing relationships between pairs of entities. Recently, Message Passing Neural Networks (MPNNs) have been employed in KGC and demonstrated superior ability in embedding learning. Current methods, however, face two major dilemmas. One focuses on learning complex entity...

Kang-Ye Wang, Peng-Wen Dai, Chuan Wang et al. · 0 citations
Preprint Sep 2026

Seeing and Solving Are Not Enough for Vision-Language Models

Vision-language models (VLMs) answer visual questions by combining visual information extraction with downstream problem solving. We investigate a fundamental question: Does an incorrect answer necessarily reflect a failure in visual extraction or problem solving? A model may succeed at both abilities when tested separ...

Zi-Heng Wang, Ming-Xuan Xie, Yi-Lin Liu et al. · 0 citations
Aug 2026

End-to-end Multi-face Forgery Detection via Progressively-explicit Queries

This paper proposes an end-to-end Transformer-based framework, termed Progressively Explicit Query Network (PEQNet), for multi-face forgery detection and localization, and introduces triple contrastive learning to model the mutual exclusivity among real, fake, and background regions.

Peng-Wen Dai, Xiaomeng Wen, Feiyang He et al. · 0 citations

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