Biwei Huang

Venues

Frequent coauthors

Papers

1. C-World: A Computer Use Agent Environment Creator
   ACL 2026 ·

   Ziqiao Xi

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2. Hybrid Self-evolving Structured Memory for Computer-Use Agents
   ACL 2026 ·

   Sibo Zhu

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3. Revisiting Differentiable Structure Learning: Inconsistency of L1 Penalty and Beyond
   AAAI 2026 ·

   Kaifeng Jin

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4. A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
   ICLR 2025 ·

   Yingyu Lin

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5. Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models
   NeurIPS 2025 ·

   Zekai Zhao

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6. Analytic DAG Constraints for Differentiable DAG Learning
   ICLR 2025 ·

   Zhen Zhang

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7. Causality Meets Locality: Provably Generalizable and Scalable Policy Learning for Networked Systems
   NeurIPS 2025 ·

   Hao Liang

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8. Differentiable Causal Discovery for Latent Hierarchical Causal Models
   ICLR 2025 ·

   Parjanya Prajakta Prashant

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9. MissScore: High-Order Score Estimation in the Presence of Missing Data
   ICML 2025 ·

   Wenqin Liu

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10. Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning
    ICLR 2025 ·

    Xinyue Wang

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11. Practical Kernel Selection for Kernel-based Conditional Independence Test
    NeurIPS 2025 ·

    Wenjie Wang

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12. Towards General Continuous Memory for Vision-Language Models
    NeurIPS 2025 ·

    Wenyi Wu

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13. Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations
    ICLR 2025 ·

    Yupei Yang

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14. A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
    ICLR 2024 ·

    Xinshuai Dong

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15. ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation
    AAAI 2024 ·

    Yuewen Sun

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16. An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series
    ICML 2024 ·

    Qiang Huang

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17. Boosting Efficiency in Task-Agnostic Exploration through Causal Knowledge
    IJCAI 2024 ·

    Yupei Yang

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18. Federated Causal Discovery from Heterogeneous Data
    ICLR 2024 ·

    Loka Li

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19. Identifiability Analysis of Linear ODE Systems with Hidden Confounders
    NeurIPS 2024 ·

    Yuanyuan Wang

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20. Identifiable Latent Polynomial Causal Models through the Lens of Change
    ICLR 2024 ·

    Yuhang Liu

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21. Identifying Latent State-Transition Processes for Individualized Reinforcement Learning
    NeurIPS 2024 ·

    Yuewen Sun

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22. Learning Discrete Concepts in Latent Hierarchical Models
    NeurIPS 2024 ·

    Lingjing Kong

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23. Natural Counterfactuals With Necessary Backtracking
    NeurIPS 2024 ·

    Guang-Yuan Hao

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24. On Causal Discovery in the Presence of Deterministic Relations
    NeurIPS 2024 ·

    Loka Li

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25. On the Parameter Identifiability of Partially Observed Linear Causal Models
    NeurIPS 2024 ·

    Xinshuai Dong

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26. Optimal Kernel Choice for Score Function-based Causal Discovery
    ICML 2024 ·

    Wenjie Wang

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27. Score-Based Causal Discovery of Latent Variable Causal Models
    ICML 2024 ·

    Ignavier Ng

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28. Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability
    ICLR 2024 ·

    Songyao Jin

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