Haoyang Li

Affiliations

Tsinghua University

papers

117

total citations

papers (16)

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts

NEURIPS 2023arXiv

citations

Graph Invariant Learning with Subgraph Co-mixup for Out-of-Distribution Generalization

AAAI 2024arXiv

citations

AutoGFM: Automated Graph Foundation Model with Adaptive Architecture Customization

ICML 2025

citations

Self-supervised Masked Graph Autoencoder via Structure-aware Curriculum

ICML 2025

citations

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

ICML 2024

citations

Multimodal Graph Neural Architecture Search under Distribution Shifts

AAAI 2024

citations

Disentangled Contrastive Learning on Graphs

NEURIPS 2021

citations

Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift

NEURIPS 2022

citations

Learning Invariant Graph Representations for Out-of-Distribution Generalization

NEURIPS 2022

citations

CurBench: Curriculum Learning Benchmark

ICML 2024

citations

VLR-Driver: Large Vision-Language-Reasoning Models for Embodied Autonomous Driving

ICCV 2025

citations

Haoyang Li

Affiliations

papers (16)

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts

Graph Invariant Learning with Subgraph Co-mixup for Out-of-Distribution Generalization

Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference

Robotic Visual Instruction

DPC: Dual-Prompt Collaboration for Tuning Vision-Language Models

Subgraph Aggregation for Out-of-Distribution Generalization on Graphs

A Sample-Level Evaluation and Generative Framework for Model Inversion Attacks

AutoGFM: Automated Graph Foundation Model with Adaptive Architecture Customization

Self-supervised Masked Graph Autoencoder via Structure-aware Curriculum

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

Multimodal Graph Neural Architecture Search under Distribution Shifts

Disentangled Contrastive Learning on Graphs

Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift

Learning Invariant Graph Representations for Out-of-Distribution Generalization

CurBench: Curriculum Learning Benchmark

VLR-Driver: Large Vision-Language-Reasoning Models for Embodied Autonomous Driving

papers (16)

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts

Graph Invariant Learning with Subgraph Co-mixup for Out-of-Distribution Generalization

Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference

Robotic Visual Instruction

DPC: Dual-Prompt Collaboration for Tuning Vision-Language Models

Subgraph Aggregation for Out-of-Distribution Generalization on Graphs

A Sample-Level Evaluation and Generative Framework for Model Inversion Attacks

AutoGFM: Automated Graph Foundation Model with Adaptive Architecture Customization

Self-supervised Masked Graph Autoencoder via Structure-aware Curriculum

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

Multimodal Graph Neural Architecture Search under Distribution Shifts

Disentangled Contrastive Learning on Graphs

Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift

Learning Invariant Graph Representations for Out-of-Distribution Generalization

CurBench: Curriculum Learning Benchmark

VLR-Driver: Large Vision-Language-Reasoning Models for Embodied Autonomous Driving