Changsheng Xu
2 indexed papers
Recent (6 mo)
2With code
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226
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Vision×1ML×1Distributed×1AI×1
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Research Timeline
2026
Disentanglement-Based Equivariant Learning for Compositional VQA
The paper proposes a novel Disentanglement-based Equivariant Learning (DEAL) framework that enhances compositional VQA by disentangling concepts and enforcing equivariant constraints, achieving state-of-the-art results on benchmark datasets.
Boosting Multimodal Federated Learning via Chained Modality Optimization
The paper proposes FedMChain, a novel federated learning framework that structures multimodal training into sequential phases to mitigate modality competition and improve model performance while reducing communication overhead.
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Papers
cs.CVcs.LGRecentJun 1, 2026
Disentanglement-Based Equivariant Learning for Compositional VQA
The paper proposes a novel Disentanglement-based Equivariant Learning (DEAL) framework that enhances compositional VQA by disentangling concepts and enforcing equivariant constraints, achieving state-…
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cs.DCcs.AIRecentJun 1, 2026