Haizhou Shi

Orcid: 0000-0002-8431-3703

According to our database1, Haizhou Shi authored at least 22 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs.
CoRR, 2024

Graph Retrieval-Augmented Generation: A Survey.
CoRR, 2024

Graph Triple Attention Network: A Decoupled Perspective.
CoRR, 2024

UniGAP: A Universal and Adaptive Graph Upsampling Approach to Mitigate Over-Smoothing in Node Classification Tasks.
CoRR, 2024

BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models.
CoRR, 2024

Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models.
CoRR, 2024

Continual Learning of Large Language Models: A Comprehensive Survey.
CoRR, 2024

GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfer Learning.
Proceedings of the ACM on Web Conference 2024, 2024

MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning.
Proceedings of the ACM on Web Conference 2024, 2024

Efficient Tuning and Inference for Large Language Models on Textual Graphs.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023
A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm.
CoRR, 2023

GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfer Learning.
CoRR, 2023

A Unified Approach to Domain Incremental Learning with Memory: Theory and Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Structure-Aware Group Discrimination with Adaptive-View Graph Encoder: A Fast Graph Contrastive Learning Framework.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
On the Efficacy of Small Self-Supervised Contrastive Models without Distillation Signals.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Federated Self-Supervised Contrastive Learning via Ensemble Similarity Distillation.
CoRR, 2021

Alleviate Representation Overlapping in Class Incremental Learning by Contrastive Class Concentration.
CoRR, 2021

CIL: Contrastive Instance Learning Framework for Distantly Supervised Relation Extraction.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Run Away From your Teacher: Understanding BYOL by a Novel Self-Supervised Approach.
CoRR, 2020

Relational Graph Learning for Grounded Video Description Generation.
Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020

Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Informative Visual Storytelling with Cross-modal Rules.
Proceedings of the 27th ACM International Conference on Multimedia, 2019


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