Jiangmeng Li
26 papers · 2022–2026 · 8 venues · across top CS/AI venues
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Research topics
Machine Learning
(19)
Artificial Intelligence
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Deep Learning
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Core AI
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Learning Types Β· Machine Learning
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Learning Types Β· Deep Learning
(8)
Architectures
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Learning Paradigms
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Optimization & Theory
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Keywords
contrastive learning
(6)
causal inference
(6)
structural causal model
(6)
self-supervised learning
(5)
representation learning
(5)
graph neural network
(4)
graph representation
(4)
backdoor adjustment
(3)
vision-language model
(3)
multi-agent communication
(2)
graph contrastive learning
(2)
domain adaptation
(2)
prompt tuning
(2)
few-shot learning
(2)
knowledge distillation
(2)
meta learning
(2)
instrumental variable
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test-time adaptation
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sequential decision making
(1)
semi-supervised learning
(1)
Papers
Doubly Debiased Test-Time Prompt Tuning for Vision-Language Models
AAAI 2026
HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning
AAAI 2026
M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference
AAAI 2026
Multi-modal Test-time Adaptation via Adaptive Probabilistic Gaussian Calibration
CVPR 2026
Test-Time Perturbation Tuning with Delayed Feedback for Vision-Language-Action Models
CVPR 2026
TMAE:Learning Targeted Multi-Agent Exploration via Causal Inference
AAAI 2026
Vision-Language Attribute Disentanglement and Reinforcement for Lifelong Person Re-Identification
CVPR 2026
DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training
ICLR 2025
Learning Invariant Causal Mechanism from Vision-Language Models
ICML 2025
On the Out-of-Distribution Generalization of Self-Supervised Learning
ICML 2025
Rethinking the Bias of Foundation Model under Long-tailed Distribution
ICML 2025
Self-Reinforcing Prototype Evolution with Dual-Knowledge Cooperation for Semi-Supervised Lifelong Person Re-Identification
ICCV 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
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
Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective
NeurIPS 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
Supporting Medical Relation Extraction via Causality-Pruned Semantic Dependency Forest
COLING 2022