Zeyang Zhang

Orcid: 0000-0003-1329-1313

Affiliations:

Tsinghua University, Beijing, China

According to our database¹, Zeyang Zhang authored at least 31 papers between 2021 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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Bibliography

2025

Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning.

[BibT_eX]

[DOI]

CoRR, June, 2025

Towards Multi-modal Graph Large Language Model.

[BibT_eX]

[DOI]

CoRR, June, 2025

Modular Machine Learning: An Indispensable Path towards New-Generation Large Language Models.

[BibT_eX]

[DOI]

CoRR, April, 2025

Disentangled Dynamic Graph Attention Network for Out-of-Distribution Sequential Recommendation.

[BibT_eX]

[DOI]

ACM Trans. Inf. Syst., January, 2025

Graph Machine Learning under Distribution Shifts: Adaptation, Generalization and Extension to LLM.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

2024

Multi-Modal Generative AI: Multi-modal LLM, Diffusion and Beyond.

[BibT_eX]

[DOI]

CoRR, 2024

Multi-sentence Video Grounding for Long Video Generation.

[BibT_eX]

[DOI]

CoRR, 2024

Causal-Aware Graph Neural Architecture Search under Distribution Shifts.

[BibT_eX]

[DOI]

CoRR, 2024

LLM-Enhanced Causal Discovery in Temporal Domain from Interventional Data.

[BibT_eX]

[DOI]

CoRR, 2024

Exploring the Potential of Large Language Models in Graph Generation.

[BibT_eX]

[DOI]

CoRR, 2024

VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

DisenStudio: Customized Multi-Subject Text-to-Video Generation with Disentangled Spatial Control.

[BibT_eX]

[DOI]

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs?

[BibT_eX]

[DOI]

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Towards Lightweight Graph Neural Network Search with Curriculum Graph Sparsification.

[BibT_eX]

[DOI]

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Disentangled Continual Graph Neural Architecture Search with Invariant Modular Supernet.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

RealTCD: Temporal Causal Discovery from Interventional Data with Large Language Model.

[BibT_eX]

[DOI]

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

LLM4VG: Large Language Models Evaluation for Video Grounding.

[BibT_eX]

[DOI]

CoRR, 2023

Out-of-Distribution Generalized Dynamic Graph Neural Network for Human Albumin Prediction.

[BibT_eX]

[DOI]

CoRR, 2023

Out-of-Distribution Generalized Dynamic Graph Neural Network with Disentangled Intervention and Invariance Promotion.

[BibT_eX]

[DOI]

CoRR, 2023

LLM4DyG: Can Large Language Models Solve Problems on Dynamic Graphs?

[BibT_eX]

[DOI]

CoRR, 2023

Large Graph Models: A Perspective.

[BibT_eX]

[DOI]

CoRR, 2023

Unsupervised Graph Neural Architecture Search with Disentangled Self-Supervision.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Dynamic Heterogeneous Graph Attention Neural Architecture Search.

[BibT_eX]

[DOI]

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

2022

Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift.

[BibT_eX]

[DOI]

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

NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search.

[BibT_eX]

[DOI]

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

Learning to Solve Travelling Salesman Problem with Hardness-Adaptive Curriculum.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Revisiting Transformation Invariant Geometric Deep Learning: Are Initial Representations All You Need?

[BibT_eX]

[DOI]

CoRR, 2021

AutoGL: A Library for Automated Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Graph Differentiable Architecture Search with Structure Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Zeyang Zhang

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