Changwen Zheng

Venues

Frequent coauthors

Papers

1. Doubly Debiased Test-Time Prompt Tuning for Vision-Language Models
   AAAI 2026 ·

   Fei Song

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2. Enhancing Large Language Models for Time-Series Forecasting via Vector-Injected In-Context Learning
   WWW 2026 ·

   Jianqi Zhang

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3. Exploring Transferability of Self-Supervised Learning by Task Conflict Calibration
   AAAI 2026 ·

   Huijie Guo

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4. Group Causal Policy Optimization for Post-Training Large Language Models
   AAAI 2026 ·

   Ziyin Gu

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5. HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning
   AAAI 2026 ·

   Qirui Ji

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6. TMAE: Learning Targeted Multi-Agent Exploration via Causal Inference
   AAAI 2026 ·

   Chuxiong Sun

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7. Advancing Complex Wide-Area Scene Understanding with Hierarchical Coresets Selection
   ACM MM 2025 ·

   Jingyao Wang

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8. Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach
   AAAI 2025 ·

   Hang Gao

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9. LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
   ICML 2025 ·

   Hang Gao

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10. Learn to Think: Bootstrapping LLM Logic Through Graph Representation Learning
    IJCAI 2025 ·

    Hang Gao

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11. Learning Invariant Causal Mechanism from Vision-Language Models
    ICML 2025 ·

    Zeen Song

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12. Learning to Think: Information-Theoretic Reinforcement Fine-Tuning for LLMs
    NeurIPS 2025 ·

    Jingyao Wang

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13. Loss of Plasticity: A New Perspective on Solving Multi-Agent Exploration for Sparse Reward Tasks
    AAMAS 2025 ·

    Zehua Zang

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14. On the Out-of-Distribution Generalization of Self-Supervised Learning
    ICML 2025 ·

    Wenwen Qiang

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15. Revisiting Communication Efficiency in Multi-Agent Reinforcement Learning from the Dimensional Analysis Perspective
    AAMAS 2025 ·

    Chuxiong Sun

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16. Towards the Causal Complete Cause of Multi-Modal Representation Learning
    ICML 2025 ·

    Jingyao Wang

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17. BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
    ICLR 2024 ·

    Jiangmeng Li

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18. Hacking Task Confounder in Meta-Learning
    IJCAI 2024 ·

    Jingyao Wang

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19. Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning
    AAAI 2024 ·

    Jiangmeng Li

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20. Not All Frequencies Are Created Equal: Towards a Dynamic Fusion of Frequencies in Time-Series Forecasting
    ACM MM 2024 ·

    Xingyu Zhang

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21. Rethinking Causal Relationships Learning in Graph Neural Networks
    AAAI 2024 ·

    Hang Gao

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22. Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective
    AAAI 2024 ·

    Qirui Ji

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23. T2MAC: Targeted and Trusted Multi-Agent Communication through Selective Engagement and Evidence-Driven Integration
    AAAI 2024 ·

    Chuxiong Sun

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