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Lixin Fan

15 papers at tracked venues · 9 at CORE A* · active 2024–2026

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Venues

EMNLP ×3AAAI ×2CVPR ×2ICDE ×2NeurIPS ×2ACL ×1ECCV ×1ECML-PKDD ×1IJCAI ×1

Frequent coauthors

Tao Fan
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Gongxi Zhu
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Jinglin Liang
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Dashan Gao
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Hanlin Gu
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Hao Yu
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Weicheng Wang
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Zhaomin Wu
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Qian Chen
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×1

Papers

  1. FedGRPO: Privately Optimizing Foundation Models with Group-Relative Rewards from Domain Clients
    AAAI 2026 ·
    Gongxi Zhu
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  2. FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion
    ACL 2026 ·
    Tao Fan
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  3. FedCoT: Federated Chain-of-Thought Distillation for Large Language Models
    EMNLP 2025 ·
    Tao Fan
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  4. FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
    CVPR 2025 ·
    Gongxi Zhu
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  5. Handling Spatial-Temporal Data Heterogeneity for Federated Continual Learning via Tail Anchor
    CVPR 2025 ·
    Hao Yu
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  6. Interactive Search with Reinforcement Learning
    ICDE 2025 ·
    Weicheng Wang
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  7. Model-based Large Language Model Customization as Service
    EMNLP 2025 ·
    Zhaomin Wu
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  8. Order-Level Attention Similarity Across Language Models: A Latent Commonality
    NeurIPS 2025 ·
    Jinglin Liang
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  9. PPC-GPT: Federated Task-Specific Compression of Large Language Models via Pruning and Chain-of-Thought Distillation
    EMNLP 2025 ·
    Tao Fan
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  10. Complementary Knowledge Distillation for Robust and Privacy-Preserving Model Serving in Vertical Federated Learning
    AAAI 2024 ·
    Dashan Gao
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  11. Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning
    ECCV 2024 ·
    Jinglin Liang
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  12. Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity
    NeurIPS 2024 ·
    Hanlin Gu
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  13. Label Privacy Source Coding in Vertical Federated Learning
    ECML-PKDD 2024 ·
    Dashan Gao
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  14. Model Trip: Enhancing Privacy and Fairness in Model Fusion Across Multi-Federations for Trustworthy Global Healthcare
    ICDE 2024 ·
    Qian Chen
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  15. Unlearning during Learning: An Efficient Federated Machine Unlearning Method
    IJCAI 2024 ·
    Hanlin Gu
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