Changwen Zheng
26 papers · 2021–2026 · 7 venues · across top CS/AI venues
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Research topics
Machine Learning
(21)
Artificial Intelligence
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Core AI
(15)
Deep Learning
(14)
Learning Types Β· Machine Learning
(14)
Architectures
(9)
Core Methods
(9)
Learning Types Β· Deep Learning
(5)
Optimization & Theory
(5)
Knowledge & Reasoning
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Learning Paradigms Β· Machine Learning
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Reasoning
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Computer Vision
(2)
Keywords
structural causal model
(8)
self-supervised learning
(7)
graph neural network
(7)
causal inference
(7)
representation learning
(5)
large language model
(5)
contrastive learning
(5)
graph representation
(4)
graph representation learning
(3)
graph contrastive learning
(2)
backdoor adjustment
(2)
meta learning
(2)
causal representation learning
(2)
bilevel optimization
(2)
knowledge distillation
(2)
spurious correlation
(2)
policy optimization
(2)
few-shot learning
(2)
instrumental variable
(2)
vision transformer
(1)
Papers
COPO: Causal-Oriented Policy Optimization for Hallucinations of MLLMs
CVPR 2026
Doubly Debiased Test-Time Prompt Tuning for Vision-Language Models
AAAI 2026
Exploring Transferability of Self-Supervised Learning by Task Conflict Calibration
AAAI 2026
Group Causal Policy Optimization for Post-Training Large Language Models
AAAI 2026
HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning
AAAI 2026
TMAE:Learning Targeted Multi-Agent Exploration via Causal Inference
AAAI 2026
Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach
AAAI 2025
Learning Invariant Causal Mechanism from Vision-Language Models
ICML 2025
Learn to Think: Bootstrapping LLM Logic Through Graph Representation Learning
IJCAI 2025
LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
ICML 2025
On the Out-of-Distribution Generalization of Self-Supervised Learning
ICML 2025
Towards the Causal Complete Cause of Multi-Modal Representation Learning
ICML 2025
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
ICLR 2024
Hacking Task Confounder in Meta-Learning
IJCAI 2024
Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning
AAAI 2024
Rethinking Causal Relationships Learning in Graph Neural Networks
AAAI 2024
Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective
AAAI 2024
T2MAC: Targeted and Trusted Multi-Agent Communication through Selective Engagement and Evidence-Driven Integration
AAAI 2024
Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from a Conditional Causal Perspective
AAAI 2023
Robust Causal Graph Representation Learning against Confounding Effects
AAAI 2023
Bootstrapping Informative Graph Augmentation via A Meta Learning Approach
IJCAI 2022
Interventional Contrastive Learning with Meta Semantic Regularizer
ICML 2022
MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning
NeurIPS 2022
MetAug: Contrastive Learning via Meta Feature Augmentation
ICML 2022
SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders
NeurIPS 2022
Toward Fully Exploiting Heterogeneous Corpus:A Decoupled Named Entity Recognition Model with Two-stage Training
ACL 2021