Jiangmeng Li

Orcid: 0000-0002-3376-1522

According to our database¹, Jiangmeng Li authored at least 78 papers between 2021 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

On the Transferability and Discriminability of Representation Learning in Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., May, 2026

Multi-modal Test-time Adaptation via Adaptive Probabilistic Gaussian Calibration.

[BibT_eX]

[DOI]

CoRR, April, 2026

Test-Time Perturbation Learning with Delayed Feedback for Vision-Language-Action Models.

[BibT_eX]

[DOI]

CoRR, April, 2026

Uniformity Preserving Transfer for Visual Prompt Tuning under Long-tailed Distribution.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., March, 2026

Vision-Language Attribute Disentanglement and Reinforcement for Lifelong Person Re-Identification.

[BibT_eX]

[DOI]

CoRR, March, 2026

AmPLe: Supporting Vision-Language Models via Adaptive-Debiased Ensemble Multi-Prompt Learning.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., February, 2026

All-in-One Image Restoration via Causal-Deconfounding Wavelet-Disentangled Prompt Network.

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[DOI]

IEEE Trans. Image Process., 2026

Visual reinforcement learning via sequential consistency preserved policy contrast from optimal transport view.

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[DOI]

Neural Networks, 2026

Towards continual low-light image enhancement through causal inference.

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[DOI]

Neural Networks, 2026

TMAE: Learning Targeted Multi-Agent Exploration via Causal Inference.

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[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Doubly Debiased Test-Time Prompt Tuning for Vision-Language Models.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Learning Complementary Knowledge via Trusted Multi-view Space Decomposition for Self-Supervised Contrastive Learning.

[BibT_eX]

[DOI]

Mach. Learn., December, 2025

C<sup>2</sup>Prompt: Class-aware Client Knowledge Interaction for Federated Continual Learning.

[BibT_eX]

[DOI]

CoRR, September, 2025

Continual Test-Time Adaptation for Single Image Defocus Deblurring via Causal Siamese Networks.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., July, 2025

BayesTTA: Continual-Temporal Test-Time Adaptation for Vision-Language Models via Gaussian Discriminant Analysis.

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[DOI]

CoRR, July, 2025

Rethinking Generalizability and Discriminability of Self-Supervised Learning from Evolutionary Game Theory Perspective.

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[DOI]

Int. J. Comput. Vis., June, 2025

Multi-Modal Learning with Bayesian-Oriented Gradient Calibration.

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[DOI]

CoRR, May, 2025

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

CoRR, May, 2025

CAIFormer: A Causal Informed Transformer for Multivariate Time Series Forecasting.

[BibT_eX]

[DOI]

CoRR, May, 2025

On the Generalization and Causal Explanation in Self-Supervised Learning.

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[DOI]

Int. J. Comput. Vis., April, 2025

Intervening on few-shot object detection based on the front-door criterion.

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[DOI]

Neural Networks, 2025

Supporting vision-language model few-shot inference with confounder-pruned knowledge prompt.

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[DOI]

Neural Networks, 2025

CellCLAT: Preserving Topology and Trimming Redundancy in Self-Supervised Cellular Contrastive Learning.

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[DOI]

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Towards the Causal Complete Cause of Multi-Modal Representation Learning.

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[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Learning Invariant Causal Mechanism from Vision-Language Models.

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Proceedings of the Forty-second International Conference on Machine Learning, 2025

On the Out-of-Distribution Generalization of Self-Supervised Learning.

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[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Rethinking the Bias of Foundation Model under Long-tailed Distribution.

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[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Causal Deconfounding for Spurious Correlation in Domain Generalization.

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[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2025

RBDN: A Robust Background Denoising Network for Weakly Supervised Temporal Language Grounding.

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[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2025

Learning Adaptive High-Frequency Semantic Guidance for Low-light Image Enhancement.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Multimedia and Expo, 2025

DenoiseVAE: Learning Molecule-Adaptive Noise Distributions for Denoising-based 3D Molecular Pre-training.

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[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Self-Reinforcing Prototype Evolution with Dual-Knowledge Cooperation for Semi-Supervised Lifelong Person Re-Identification.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

MAP: Supporting Multimodal Knowledge Graph Completion via Augmented Modality Alignment and Instance Preserving.

[BibT_eX]

[DOI]

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

2024

Physics-Guided Optical Simulation and PSF Analysis for Remote Sensing Images Deblurring.

[BibT_eX]

[DOI]

IEEE Trans. Geosci. Remote. Sens., 2024

Unsupervised social event detection via hybrid graph contrastive learning and reinforced incremental clustering.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2024

Introducing diminutive causal structure into graph representation learning.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2024

Neuromodulated Meta-Learning.

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[DOI]

CoRR, 2024

Rethinking Meta-Learning from a Learning Lens.

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[DOI]

CoRR, 2024

On the Causal Sufficiency and Necessity of Multi-Modal Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Revisiting Spurious Correlation in Domain Generalization.

[BibT_eX]

[DOI]

CoRR, 2024

Teleporter Theory: A General and Simple Approach for Modeling Cross-World Counterfactual Causality.

[BibT_eX]

[DOI]

CoRR, 2024

Interventional Imbalanced Multi-Modal Representation Learning via β-Generalization Front-Door Criterion.

[BibT_eX]

[DOI]

CoRR, 2024

Explicitly Modeling Universality into Self-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Graph Partial Label Learning with Potential Cause Discovering.

[BibT_eX]

[DOI]

CoRR, 2024

Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

MSI: Multi-modal Recommendation via Superfluous Semantics Discarding and Interaction Preserving.

[BibT_eX]

[DOI]

Proceedings of the 2024 International Conference on Multimedia Retrieval, 2024

BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Demo:SCDRL: Scalable and Customized Distributed Reinforcement Learning System.

[BibT_eX]

[DOI]

Chuxiong Sun

Wenwen Qiang

Jiangmeng Li

Proceedings of the 44th IEEE International Conference on Distributed Computing Systems, 2024

T2MAC: Targeted and Trusted Multi-Agent Communication through Selective Engagement and Evidence-Driven Integration.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Hierarchical Topology Isomorphism Expertise Embedded Graph Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Rethinking Causal Relationships Learning in Graph Neural Networks.

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[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Information theory-guided heuristic progressive multi-view coding.

[BibT_eX]

[DOI]

Neural Networks, October, 2023

Modeling Multiple Views via Implicitly Preserving Global Consistency and Local Complementarity.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., July, 2023

Meta Attention-Generation Network for Cross-Granularity Few-Shot Learning.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., May, 2023

Robust Local Preserving and Global Aligning Network for Adversarial Domain Adaptation.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., March, 2023

Rule Learning over Knowledge Graphs: A Review.

[BibT_eX]

[DOI]

Hong Wu

Zhe Wang

Kewen Wang

Pouya Ghiasnezhad Omran

Jiangmeng Li

TGDK, 2023

M2HGCL: Multi-Scale Meta-Path Integrated Heterogeneous Graph Contrastive Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Atomic and Subgraph-aware Bilateral Aggregation for Molecular Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Introducing Expertise Logic into Graph Representation Learning from A Causal Perspective.

[BibT_eX]

[DOI]

CoRR, 2023

M<sup>2</sup>HGCL: Multi-scale Meta-path Integrated Heterogeneous Graph Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Advanced Data Mining and Applications - 19th International Conference, 2023

Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from a Conditional Causal Perspective.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Robust Causal Graph Representation Learning against Confounding Effects.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

RHMC: Modeling consistent information from deep multiple views via Regularized and Hybrid Multiview Coding.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2022

Multi-view representation learning from local consistency and global alignment.

[BibT_eX]

[DOI]

Neurocomputing, 2022

A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language.

[BibT_eX]

[DOI]

CoRR, 2022

Supporting Vision-Language Model Inference with Causality-pruning Knowledge Prompt.

[BibT_eX]

[DOI]

CoRR, 2022

Self-supervised Graph Learning with Segmented Graph Channels.

[BibT_eX]

[DOI]

Hang Gao

Jiangmeng Li

Changwen Zheng

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bootstrapping Informative Graph Augmentation via A Meta Learning Approach.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Interventional Contrastive Learning with Meta Semantic Regularizer.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

MetAug: Contrastive Learning via Meta Feature Augmentation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Weight-Aware Graph Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Supporting Medical Relation Extraction via Causality-Pruned Semantic Dependency Forest.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

Auxiliary task guided mean and covariance alignment network for adversarial domain adaptation.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2021

Short Text Clustering with a Deep Multi-embedded Self-supervised Model.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Jiangmeng Li

Timeline

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