← Authors

Kun Zhang

213 papers · 2008–2026 · 17 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (31) 🐝 Cross-Pollinator (12) πŸƒ Academic Marathon (17) 🌍 Conference Polyglot (17) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (8) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🏠 Conference Loyalist (26) πŸ‘‘ Domain Dominant (38) 🀝 Dynamic Duo (43) πŸ† Keyword Champion (2) πŸ”¬ Deep Specialist (13) πŸ† Grand Slam πŸ‘‘ Triple Crown πŸ‘₯ Mega-Team (27) 🧬 Topic Evolution πŸ”₯ Unstoppable (11) ⚑ Prolific Year (32) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (111) ❓ The Questioner (3) πŸ’Ž Century Club (210) πŸš€ Conference Pioneer

Conferences

NIPS (50) ICML (36) ICLR (35) AAAI (29) CVPR (11) AISTATS (9) ACL (8) IJCAI (8) JMLR (7) ICCV (4) EMNLP (4) CLEAR (4) COLING (2) ACML (2) UAI (2) ECCV (1) INTERSPEECH (1)

Top co-authors

Mingming Gong (43) Biwei Huang (36) Ignavier Ng (27) Guangyi Chen (27) Yujia Zheng (22) Tongliang Liu (21) Ruichu Cai (17) Xinshuai Dong (15) Peter Spirtes (14) Shaoan Xie (13)

Research topics

Applications (1)

Keywords

causal discovery (47) causal inference (28) domain adaptation (16) representation learning (13) causal structure (13) latent variable (13) unsupervised learning (10) independent component analysis (9) latent variable model (8) graphical model (8) distribution shift (8) directed acyclic graph (6) structural equation model (6) structure learning (6) image-to-image translation (5) continuous optimization (5) generative adversarial network (5) reinforcement learning (5) contrastive learning (5) generative model (5)

Papers

Horizontal and Vertical Federated Causal Structure Learning via Higher-order Cumulants AAAI 2026
Revisiting Differentiable Structure Learning: Inconsistency of L1 Penalty and Beyond AAAI 2026
Socrates or Smartypants: Testing Logic Reasoning Capabilities of Large Language Models with Logic Programming-Based Test Oracles AAAI 2026
DH-Set: Improving Vision-Language Alignment with Diverse and Hybrid Set-Embeddings Learning CVPR 2025
SmartCLIP: Modular Vision-language Alignment with Identification Guarantees CVPR 2025
OCRT: Boosting Foundation Models in the Open World with Object-Concept-Relation Triad CVPR 2025
Nonparametric Factor Analysis and Beyond AISTATS 2025
Type Information-Assisted Self-Supervised Knowledge Graph Denoising AISTATS 2025
Causal Representation Learning from General Environments under Nonparametric Mixing AISTATS 2025
A Sample Efficient Conditional Independence Test in the Presence of Discretization ICML 2025
A General Representation-Based Approach to Multi-Source Domain Adaptation ICML 2025
Extracting Rare Dependence Patterns via Adaptive Sample Reweighting ICML 2025
Fairness on Principal Stratum: A New Perspective on Counterfactual Fairness ICML 2025
Permutation-based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data ICML 2025
Latent Variable Causal Discovery under Selection Bias ICML 2025
Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations ICML 2025
Voices of Her: Analyzing Gender Differences in the AI Publication World ACL 2025
Hierarchy-Aware Pseudo Word Learning with Text Adaptation for Zero-Shot Composed Image Retrieval ICCV 2025
TIU-Bench: A Benchmark for Evaluating Large Multimodal Models on Text-rich Image Understanding EMNLP 2025
Identification of Intermittent Temporal Latent Process ICLR 2025
When Selection Meets Intervention: Additional Complexities in Causal Discovery ICLR 2025
Causal Graph Transformer for Treatment Effect Estimation Under Unknown Interference ICLR 2025
Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning ICLR 2025
Empowering LLMs with Logical Reasoning: A Comprehensive Survey IJCAI 2025
MVP-CBM: Multi-layer Visual Preference-enhanced Concept Bottleneck Model for Explainable Medical Image Classification IJCAI 2025
On the Identification of Temporal Causal Representation with Instantaneous Dependence ICLR 2025
Differentiable Causal Discovery for Latent Hierarchical Causal Models ICLR 2025
Analytic DAG Constraints for Differentiable DAG Learning ICLR 2025
A Conditional Independence Test in the Presence of Discretization ICLR 2025
Noisy Test-Time Adaptation in Vision-Language Models ICLR 2025
Learning Graph Invariance by Harnessing Spuriosity ICLR 2025
A Robust Method to Discover Causal or Anticausal Relation ICLR 2025
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery ICLR 2025
Flow: Modularized Agentic Workflow Automation ICLR 2025
Causal Representation Learning from Multimodal Biomedical Observations ICLR 2025
Prompting Fairness: Integrating Causality to Debias Large Language Models ICLR 2025
Nonparametric Identification of Latent Concepts ICML 2025
Learning Vision and Language Concepts for Controllable Image Generation ICML 2025
Continual Unsupervised Generative Modelling via Online Optimal Transport AAAI 2025
Dynamic Expansion Diffusion Learning for Lifelong Generative Modelling AAAI 2025
Reflection-Window Decoding: Text Generation with Selective Refinement ICML 2025
Unmasking Style Sensitivity: A Causal Analysis of Bias Evaluation Instability in Large Language Models ACL 2025
Structured Discourse Representation for Factual Consistency Verification ACL 2025
MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning ACL 2025
A General Knowledge Injection Framework for ICD Coding ACL 2025
Discovery of the Hidden World with Large Language Models NIPS 2024
Towards Understanding Extrapolation: a Causal Lens NIPS 2024
Identifying Latent State-Transition Processes for Individualized Reinforcement Learning NIPS 2024
On Causal Discovery in the Presence of Deterministic Relations NIPS 2024
A Local Method for Satisfying Interventional Fairness with Partially Known Causal Graphs NIPS 2024
Procedural Fairness Through Decoupling Objectionable Data Generating Components ICLR 2024
LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer ICLR 2024
Structural Estimation of Partially Observed Linear Non-Gaussian Acyclic Model: A Practical Approach with Identifiability ICLR 2024
Federated Causal Discovery from Heterogeneous Data ICLR 2024
Identifiable Latent Polynomial Causal Models through the Lens of Change ICLR 2024
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables ICLR 2024
Identification of Necessary Semantic Undertakers in the Causal View for Image-Text Matching AAAI 2024
Detecting and Identifying Selection Structure in Sequential Data ICML 2024
Causal Representation Learning from Multiple Distributions: A General Setting ICML 2024
Empowering Graph Invariance Learning with Deep Spurious Infomax ICML 2024
Optimal Kernel Choice for Score Function-based Causal Discovery ICML 2024
Score-Based Causal Discovery of Latent Variable Causal Models ICML 2024
On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data ICML 2024
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process ICML 2024
S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment AAAI 2024
ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation AAAI 2024
Tree-of-Reasoning Question Decomposition for Complex Question Answering with Large Language Models AAAI 2024
Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants AAAI 2024
Local Causal Discovery with Linear non-Gaussian Cyclic Models AISTATS 2024
Structure Learning with Continuous Optimization: A Sober Look and Beyond CLEAR 2024
Visual-Linguistic Dependency Encoding for Image-Text Retrieval COLING 2024
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables JMLR 2024
Identifiability and Asymptotics in Learning Homogeneous Linear ODE Systems from Discrete Observations JMLR 2024
Causal-learn: Causal Discovery in Python JMLR 2024
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View ICLR 2024
Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions ICLR 2024
Identifying Selections for Unsupervised Subtask Discovery NIPS 2024
Natural Counterfactuals With Necessary Backtracking NIPS 2024
Learning Discrete Latent Variable Structures with Tensor Rank Conditions NIPS 2024
On the Parameter Identifiability of Partially Observed Linear Causal Models NIPS 2024
Learning Discrete Concepts in Latent Hierarchical Models NIPS 2024
Causal Temporal Representation Learning with Nonstationary Sparse Transition NIPS 2024
Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization NIPS 2024
PLOT: Prompt Learning with Optimal Transport for Vision-Language Models ICLR 2023
Identification of Nonlinear Latent Hierarchical Models NIPS 2023
Temporally Disentangled Representation Learning under Unknown Nonstationarity NIPS 2023
Generalizing Nonlinear ICA Beyond Structural Sparsity NIPS 2023
Disentangling Cognitive Diagnosis with Limited Exercise Labels NIPS 2023
Learning World Models with Identifiable Factorization NIPS 2023
Subspace Identification for Multi-Source Domain Adaptation NIPS 2023
On the Identifiability of Sparse ICA without Assuming Non-Gaussianity NIPS 2023
Counterfactual Generation with Identifiability Guarantees NIPS 2023
Fair Representation Learning for Recommendation: A Mutual Information Perspective AAAI 2023
Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks (Student Abstract) AAAI 2023
Uncertainty Guided Label Denoising for Document-level Distant Relation Extraction ACL 2023
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise CLEAR 2023
Scalable Causal Discovery with Score Matching CLEAR 2023
Understanding Masked Autoencoders via Hierarchical Latent Variable Models CVPR 2023
Unpaired Image-to-Image Translation With Shortest Path Regularization CVPR 2023
Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction CVPR 2023
SmartBrush: Text and Shape Guided Object Inpainting With Diffusion Model CVPR 2023
ReFSQL: A Retrieval-Augmentation Framework for Text-to-SQL Generation EMNLP 2023
FactSpotter: Evaluating the Factual Faithfulness of Graph-to-Text Generation EMNLP 2023
Tem-Adapter: Adapting Image-Text Pretraining for Video Question Answer ICCV 2023
Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems ICLR 2023
Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors ICLR 2023
GAIN: On the Generalization of Instructional Action Understanding ICLR 2023
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks ICLR 2023
Causal Balancing for Domain Generalization ICLR 2023
Multi-domain image generation and translation with identifiability guarantees ICLR 2023
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants ICML 2023
Evolving Semantic Prototype Improves Generative Zero-Shot Learning ICML 2023
Model Transferability with Responsive Decision Subjects ICML 2023
Identifiability of Label Noise Transition Matrix ICML 2023
Feature Expansion for Graph Neural Networks ICML 2023
Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise? ICML 2023
Identification of Linear Non-Gaussian Latent Hierarchical Structure ICML 2022
Partial disentanglement for domain adaptation ICML 2022
Action-Sufficient State Representation Learning for Control with Structural Constraints ICML 2022
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts ICML 2022
Factored Adaptation for Non-Stationary Reinforcement Learning NIPS 2022
Unsupervised Image-to-Image Translation with Density Changing Regularization NIPS 2022
Independence Testing-Based Approach to Causal Discovery under Measurement Error and Linear Non-Gaussian Models NIPS 2022
Temporally Disentangled Representation Learning NIPS 2022
Optimal Transport for Causal Discovery ICLR 2022
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning ICLR 2022
Maximum Spatial Perturbation Consistency for Unpaired Image-to-Image Translation CVPR 2022
Alleviating Semantics Distortion in Unsupervised Low-Level Image-to-Image Translation via Structure Consistency Constraint CVPR 2022
Towards Federated Bayesian Network Structure Learning with Continuous Optimization AISTATS 2022
Meta-CQG: A Meta-Learning Framework for Complex Question Generation over Knowledge Bases COLING 2022
On the Convergence of Continuous Constrained Optimization for Structure Learning AISTATS 2022
Attainability and Optimality: The Equalized Odds Fairness Revisited CLEAR 2022
Causal Discovery in Linear Latent Variable Models Subject to Measurement Error NIPS 2022
Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis ACL 2022
Counterfactual Fairness with Partially Known Causal Graph NIPS 2022
Invariant Action Effect Model for Reinforcement Learning AAAI 2022
Identification of Linear Latent Variable Model with Arbitrary Distribution AAAI 2022
Residual Similarity Based Conditional Independence Test and Its Application in Causal Discovery AAAI 2022
Show Your Faith: Cross-Modal Confidence-Aware Network for Image-Text Matching AAAI 2022
CausalNLP Tutorial: An Introduction to Causality for Natural Language Processing EMNLP 2022
Negative-Aware Attention Framework for Image-Text Matching CVPR 2022
Adversarial Robustness Through the Lens of Causality ICLR 2022
Conditional Contrastive Learning with Kernel ICLR 2022
Learning Temporally Causal Latent Processes from General Temporal Data ICLR 2022
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models NIPS 2022
Latent Hierarchical Causal Structure Discovery with Rank Constraints NIPS 2022
On the Identifiability of Nonlinear ICA: Sparsity and Beyond NIPS 2022
Truncated Matrix Power Iteration for Differentiable DAG Learning NIPS 2022
$K^2$-GNN: Multiple Users’ Comments Integration with Probabilistic K-Hop Knowledge Graph Neural Networks ACML 2021
DAE-GAN: Dynamic Aspect-Aware GAN for Text-to-Image Synthesis ICCV 2021
Unaligned Image-to-Image Translation by Learning to Reweight ICCV 2021
Making the Relation Matters: Relation of Relation Learning Network for Sentence Semantic Matching AAAI 2021
Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification AAAI 2021
Improving Causal Discovery By Optimal Bayesian Network Learning AAAI 2021
Testing Independence Between Linear Combinations for Causal Discovery AAAI 2021
DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding AAAI 2021
Domain Adaptation with Invariant Representation Learning: What Transformations to Learn? NIPS 2021
Identification of Partially Observed Linear Causal Models: Graphical Conditions for the Non-Gaussian and Heterogeneous Cases NIPS 2021
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions NIPS 2021
Instance-dependent Label-noise Learning under a Structural Causal Model NIPS 2021
Progressive Open-Domain Response Generation with Multiple Controllable Attributes IJCAI 2021
PIDS: An Intelligent Electric Power Management Platform AAAI 2020
LTF: A Label Transformation Framework for Correcting Label Shift ICML 2020
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs NIPS 2020
Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach AAAI 2020
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs NIPS 2020
Re-Weighted Interval Loss for Handling Data Imbalance Problem of End-to-End Keyword Spotting INTERSPEECH 2020
Compressed Self-Attention for Deep Metric Learning AAAI 2020
How do fair decisions fare in long-term qualification? NIPS 2020
Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables JMLR 2020
Label-Noise Robust Domain Adaptation ICML 2020
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs ICML 2020
Causal Discovery from Heterogeneous/Nonstationary Data JMLR 2020
A Causal View on Robustness of Neural Networks NIPS 2020
Domain Adaptation as a Problem of Inference on Graphical Models NIPS 2020
Generative-Discriminative Complementary Learning AAAI 2020
Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets AAAI 2020
Gated Convolutional Networks with Hybrid Connectivity for Image Classification AAAI 2020
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models ICML 2019
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees AAAI 2019
DRr-Net: Dynamic Re-Read Network for Sentence Semantic Matching AAAI 2019
Causal Discovery with General Non-Linear Relationships using Non-Linear ICA UAI 2019
Domain Generalization via Multidomain Discriminant Analysis UAI 2019
Neural News Recommendation with Long- and Short-term User Representations ACL 2019
Causal Discovery in the Presence of Missing Data AISTATS 2019
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation NIPS 2019
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering NIPS 2019
Triad Constraints for Learning Causal Structure of Latent Variables NIPS 2019
Likelihood-Free Overcomplete ICA and Applications In Causal Discovery NIPS 2019
Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping CVPR 2019
Causal Discovery with Cascade Nonlinear Additive Noise Model IJCAI 2019
Learning Disentangled Semantic Representation for Domain Adaptation IJCAI 2019
Intelligent Decision Support for Improving Power Management IJCAI 2019
Twin Auxilary Classifiers GAN NIPS 2019
Data-Driven Approach to Multiple-Source Domain Adaptation AISTATS 2019
Low-Dimensional Density Ratio Estimation for Covariate Shift Correction AISTATS 2019
On Learning Invariant Representations for Domain Adaptation ICML 2019
Causal Discovery from Discrete Data using Hidden Compact Representation NIPS 2018
Deep Domain Generalization via Conditional Invariant Adversarial Networks ECCV 2018
Modeling Dynamic Missingness of Implicit Feedback for Recommendation NIPS 2018
Multi-domain Causal Structure Learning in Linear Systems NIPS 2018
Learning Causal Structures Using Regression Invariance NIPS 2017
Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination IJCAI 2017
Domain Adaptation with Conditional Transferable Components ICML 2016
Identification of Time-Dependent Causal Model: A Gaussian Process Treatment IJCAI 2015
Discovering Temporal Causal Relations from Subsampled Data ICML 2015
Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components ICML 2015
Domain Adaptation under Target and Conditional Shift ICML 2013
Causal discovery with scale-mixture model for spatiotemporal variance dependencies NIPS 2012
A General Linear Non-Gaussian State-Space Model: Identifiability, Identification, and Applications ACML 2011
Probabilistic latent variable models for distinguishing between cause and effect NIPS 2010
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity JMLR 2010
Minimal Nonlinear Distortion Principle for Nonlinear Independent Component Analysis JMLR 2008