PPaperPicks

Kun Zhang

Carnegie Mellon University, Department of Philosophy, Pittsburgh, PA, USA

81 papers at tracked venues · 75 at CORE A* · active 2024–2026

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Venues

NeurIPS ×23ICLR ×22ICML ×17AAAI ×5AISTATS ×4ACL ×3CVPR ×2WWW ×2ICDM ×1IJCAI ×1SIGKDD ×1

Frequent coauthors

Haoyue Dai
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Yujia Zheng
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Zijian Li
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Shaoan Xie
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Xiangchen Song
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Ignavier Ng
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Yuewen Sun
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Guangyi Chen
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Tianjun Yao
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Xinshuai Dong
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Wei Chen
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Fengxiang Cheng
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Papers

  1. Advancing Reasoning in Diffusion Language Models with Denoising Process Rewards
    ACL 2026 ·
    Shaoan Xie
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  2. Horizontal and Vertical Federated Causal Structure Learning via Higher-order Cumulants
    AAAI 2026 ·
    Wei Chen
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  3. Mechanistic Interpretability Should Prioritize Feature Consistency in Sparse Autoencoders
    ACL 2026 ·
    Xiangchen Song
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  4. Revisiting Differentiable Structure Learning: Inconsistency of L1 Penalty and Beyond
    AAAI 2026 ·
    Kaifeng Jin
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  5. Text Embedding as Treatment: A Meta Causal Approach for Robust Sentiment Classification
    ACL 2026 ·
    Fengxiang Cheng
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  6. A General Representation-Based Approach to Multi-Source Domain Adaptation
    ICML 2025 ·
    Ignavier Ng
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  7. A Robust Method to Discover Causal or Anticausal Relation
    ICLR 2025 ·
    Yu Yao
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  8. A Sample Efficient Conditional Independence Test in the Presence of Discretization
    ICML 2025 ·
    Boyang Sun
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  9. A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
    ICLR 2025 ·
    Yingyu Lin
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  10. Analytic DAG Constraints for Differentiable DAG Learning
    ICLR 2025 ·
    Zhen Zhang
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  11. Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference
    ICLR 2025 ·
    Anpeng Wu
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  12. Causal Representation Learning from General Environments under Nonparametric Mixing
    AISTATS 2025 ·
    Ignavier Ng
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  13. Causal Representation Learning from Multimodal Biomedical Observations
    ICLR 2025 ·
    Yuewen Sun
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  14. CausalVerse: Benchmarking Causal Representation Learning with Configurable High-Fidelity Simulations
    NeurIPS 2025 ·
    Guangyi Chen
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  15. Classifying Treatment Responders: Bounds and Algorithms
    SIGKDD 2025 ·
    Anpeng Wu
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  16. Detecting Generated Images by Fitting Natural Image Distributions
    NeurIPS 2025 ·
    Yonggang Zhang
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  17. Differentiable Causal Discovery for Latent Hierarchical Causal Models
    ICLR 2025 ·
    Parjanya Prajakta Prashant
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  18. Empowering LLMs with Logical Reasoning: A Comprehensive Survey
    IJCAI 2025 ·
    Fengxiang Cheng
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  19. Extracting Rare Dependence Patterns via Adaptive Sample Reweighting
    ICML 2025 ·
    Yiqing Li
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  20. Fairness on Principal Stratum: A New Perspective on Counterfactual Fairness
    ICML 2025 ·
    Haoxuan Li
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  21. Flow: Modularized Agentic Workflow Automation
    ICLR 2025 ·
    Boye Niu
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  22. Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders
    NeurIPS 2025 ·
    Gongxu Luo
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  23. Identification of Intermittent Temporal Latent Process
    ICLR 2025 ·
    Yuke Li
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  24. Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations
    ICML 2025 ·
    Zhengming Chen
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  25. LLM Interpretability with Identifiable Temporal-Instantaneous Representation
    NeurIPS 2025 ·
    Xiangchen Song
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  26. Latent Variable Causal Discovery under Selection Bias
    ICML 2025 ·
    Haoyue Dai
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  27. Learning Counterfactual Outcomes Under Rank Preservation
    NeurIPS 2025 ·
    Peng Wu
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  28. Learning Disentangled Representation for Multi-Modal Time-Series Sensing Signals
    WWW 2025 ·
    Ruichu Cai
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  29. Learning Graph Invariance by Harnessing Spuriosity
    ICLR 2025 ·
    Tianjun Yao
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  30. Learning Vision and Language Concepts for Controllable Image Generation
    ICML 2025 ·
    Shaoan Xie
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  31. Noisy Test-Time Adaptation in Vision-Language Models
    ICLR 2025 ·
    Chentao Cao
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  32. Nonparametric Factor Analysis and Beyond
    AISTATS 2025 ·
    Yujia Zheng
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  33. Nonparametric Identification of Latent Concepts
    ICML 2025 ·
    Yujia Zheng
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  34. OCRT: Boosting Foundation Models in the Open World with Object-Concept-Relation Triad
    CVPR 2025 ·
    Luyao Tang
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  35. On the Identification of Temporal Causal Representation with Instantaneous Dependence
    ICLR 2025 ·
    Zijian Li
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  36. Online Time Series Forecasting with Theoretical Guarantees
    NeurIPS 2025 ·
    Zijian Li
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  37. Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data
    ICML 2025 ·
    Xinshuai Dong
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  38. Practical Kernel Selection for Kernel-based Conditional Independence Test
    NeurIPS 2025 ·
    Wenjie Wang
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  39. Prompting Fairness: Integrating Causality to Debias Large Language Models
    ICLR 2025 ·
    Jingling Li
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  40. Reflection-Window Decoding: Text Generation with Selective Refinement
    ICML 2025 ·
    Zeyu Tang
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  41. SmartCLIP: Modular Vision-language Alignment with Identification Guarantees
    CVPR 2025 ·
    Shaoan Xie
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  42. Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
    ICLR 2025 ·
    Zijian Li
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  43. The third pillar of causal analysis? A measurement perspective on causal representations
    NeurIPS 2025 ·
    Dingling Yao
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  44. Thought Communication in Multiagent Collaboration
    NeurIPS 2025 ·
    Yujia Zheng
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  45. Towards Accurate Time Series Forecasting via Implicit Decoding
    NeurIPS 2025 ·
    Xinyu Li
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  46. Towards Identifiability of Hierarchical Temporal Causal Representation Learning
    NeurIPS 2025 ·
    Zijian Li
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  47. Towards Self-Refinement of Vision-Language Models with Triangular Consistency
    NeurIPS 2025 ·
    Yunlong Deng
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  48. Type Information-Assisted Self-Supervised Knowledge Graph Denoising
    AISTATS 2025 ·
    Jiaqi Sun
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  49. When Selection Meets Intervention: Additional Complexities in Causal Discovery
    ICLR 2025 ·
    Haoyue Dai
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  50. A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
    ICLR 2024 ·
    Xinshuai Dong
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  51. ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation
    AAAI 2024 ·
    Yuewen Sun
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  52. CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process
    ICML 2024 ·
    Guangyi Chen
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  53. Causal Representation Learning from Multiple Distributions: A General Setting
    ICML 2024 · Kun Zhang
  54. Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions
    ICLR 2024 ·
    Xiu-Chuan Li
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  55. Causal Temporal Representation Learning with Nonstationary Sparse Transition
    NeurIPS 2024 ·
    Xiangchen Song
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  56. Detecting and Identifying Selection Structure in Sequential Data
    ICML 2024 ·
    Yujia Zheng
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  57. Discovery of the Hidden World with Large Language Models
    NeurIPS 2024 ·
    Chenxi Liu
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  58. Empowering Graph Invariance Learning with Deep Spurious Infomax
    ICML 2024 ·
    Tianjun Yao
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  59. Federated Causal Discovery from Heterogeneous Data
    ICLR 2024 ·
    Loka Li
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  60. Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View
    ICLR 2024 ·
    Haoyue Dai
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  61. IEEE International Conference on Data Mining, ICDM 2024, Abu Dhabi, United Arab Emirates, December 9-12, 2024
    ICDM 2024 ·
    Elena Baralis
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  62. Identifiable Latent Polynomial Causal Models through the Lens of Change
    ICLR 2024 ·
    Yuhang Liu
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  63. Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants
    AAAI 2024 ·
    Wei Chen
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  64. Identifying Latent State-Transition Processes for Individualized Reinforcement Learning
    NeurIPS 2024 ·
    Yuewen Sun
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  65. Identifying Selections for Unsupervised Subtask Discovery
    NeurIPS 2024 ·
    Yiwen Qiu
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  66. LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer
    ICLR 2024 ·
    Guangyi Chen
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  67. Learning Discrete Concepts in Latent Hierarchical Models
    NeurIPS 2024 ·
    Lingjing Kong
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  68. Learning Discrete Latent Variable Structures with Tensor Rank Conditions
    NeurIPS 2024 ·
    Zhengming Chen
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  69. Local Causal Discovery with Linear non-Gaussian Cyclic Models
    AISTATS 2024 ·
    Haoyue Dai
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  70. MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification
    WWW 2024 ·
    Tianjun Yao
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  71. Natural Counterfactuals With Necessary Backtracking
    NeurIPS 2024 ·
    Guang-Yuan Hao
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  72. Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization
    NeurIPS 2024 ·
    Zhikang Chen
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  73. On Causal Discovery in the Presence of Deterministic Relations
    NeurIPS 2024 ·
    Loka Li
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  74. On the Parameter Identifiability of Partially Observed Linear Causal Models
    NeurIPS 2024 ·
    Xinshuai Dong
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  75. On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data
    ICML 2024 ·
    Shunxing Fan
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  76. Optimal Kernel Choice for Score Function-based Causal Discovery
    ICML 2024 ·
    Wenjie Wang
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  77. Procedural Fairness Through Decoupling Objectionable Data Generating Components
    ICLR 2024 ·
    Zeyu Tang
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  78. S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment
    AAAI 2024 ·
    Sheng Zhang
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  79. Score-Based Causal Discovery of Latent Variable Causal Models
    ICML 2024 ·
    Ignavier Ng
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  80. Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability
    ICLR 2024 ·
    Songyao Jin
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  81. Towards Understanding Extrapolation: a Causal Lens
    NeurIPS 2024 ·
    Lingjing Kong
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