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← Authors

Changwen Zheng

26 papers · 2021–2026 · 7 conferences · across top CS/AI conferences

Achievements

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+9 more ↓ πŸƒ Academic Marathon (5) 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) 🐝 Cross-Pollinator (7) 🌈 Renaissance Researcher (7)
πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (30) 🧭 Keyword Pioneer 🀝 Dynamic Duo (14) πŸ† Grand Slam ⚑ Prolific Year (6) πŸ’Ž Century Club (21) πŸ—ƒοΈ Keyword Collector (68) πŸ”₯ Unstoppable (5)

Conferences

AAAI (12) ICML (6) IJCAI (3) NIPS (2) ACL (1) ICLR (1) IJCNLP (1)

Top co-authors

Jiangmeng Li (17) Wenwen Qiang (15) Hang Gao (7) Fuchun Sun (6) Hui Xiong (5) Jingyao Wang (5) Lingyu Si (4) Huaping Liu (4) Chuxiong Sun (4) Yifan Jin (4)

Keywords

graph neural network (6) causal inference (6) structural causal model (6) self-supervised learning (6) contrastive learning (5) graph representation (4) representation learning (4) graph representation learning (3) large language model (3) knowledge distillation (2) meta learning (2) bi-level optimization (2) backdoor adjustment (2) causal representation learning (2) graph contrastive learning (2) vision transformer (1) semantic segmentation (1) object detection (1) entropy minimization (1) vision-language model (1)

Papers

Doubly Debiased Test-Time Prompt Tuning for Vision-Language Models AAAI 2026 Group Causal Policy Optimization for Post-Training Large Language Models AAAI 2026 TMAE:Learning Targeted Multi-Agent Exploration via Causal Inference AAAI 2026 HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning AAAI 2026 Exploring Transferability of Self-Supervised Learning by Task Conflict Calibration AAAI 2026 LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification ICML 2025 Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach AAAI 2025 On the Out-of-Distribution Generalization of Self-Supervised Learning ICML 2025 Learning Invariant Causal Mechanism from Vision-Language Models ICML 2025 Towards the Causal Complete Cause of Multi-Modal Representation Learning ICML 2025 Learn to Think: Bootstrapping LLM Logic Through Graph Representation Learning IJCAI 2025 BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction ICLR 2024 Rethinking Causal Relationships Learning in Graph Neural Networks AAAI 2024 Hacking Task Confounder in Meta-Learning IJCAI 2024 Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning AAAI 2024 T2MAC: Targeted and Trusted Multi-Agent Communication through Selective Engagement and Evidence-Driven Integration AAAI 2024 Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective AAAI 2024 Robust Causal Graph Representation Learning against Confounding Effects AAAI 2023 Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from a Conditional Causal Perspective AAAI 2023 Bootstrapping Informative Graph Augmentation via A Meta Learning Approach IJCAI 2022 SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders NIPS 2022 MetAug: Contrastive Learning via Meta Feature Augmentation ICML 2022 Interventional Contrastive Learning with Meta Semantic Regularizer ICML 2022 MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning NIPS 2022 Toward Fully Exploiting Heterogeneous Corpus:A Decoupled Named Entity Recognition Model with Two-stage Training IJCNLP 2021 Toward Fully Exploiting Heterogeneous Corpus:A Decoupled Named Entity Recognition Model with Two-stage Training ACL 2021