Haoyang Li
33 papers · 2021–2026 · 10 conferences · across top CS/AI conferences
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ICML (6)
NIPS (5)
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ICCV (2)
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graph neural network
(8)
domain generalization
(6)
out-of-distribution generalization
(4)
transfer learning
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distribution shift
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invariant learning
(3)
graph representation learning
(3)
invariant subgraph
(2)
large language model
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subgraph extraction
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vision-language model
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dynamic graph
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few-shot learning
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invariant pattern
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spurious correlation
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recommender system
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contrastive learning
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direct preference optimization
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curriculum learning
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adversarial robustness
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Papers
Keep On Going: Learning Robust Humanoid Motion Skills via Selective Adversarial Training
AAAI 2026
Persona-EΒ²: A Human-Grounded Dataset for Personality-Shaped Emotional Responses to Textual Events
ACL 2026
Class-feature Watermark: A Resilient Black-box Watermark Against Model Extraction Attacks
AAAI 2026
Robotic Visual Instruction
CVPR 2025
Diffusion Dynamics Models with Generative State Estimation for Cloth Manipulation
CORL 2025
A Sample-Level Evaluation and Generative Framework for Model Inversion Attacks
AAAI 2025
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
AAAI 2025
Uncovering the Impact of Chain-of-Thought Reasoning for Direct Preference Optimization: Lessons from Text-to-SQL
ACL 2025
LLMs Caught in the Crossfire: Malware Requests and Jailbreak Challenges
ACL 2025
Exposing Numeracy Gaps: A Benchmark to Evaluate Fundamental Numerical Abilities in Large Language Models
ACL 2025
DPC: Dual-Prompt Collaboration for Tuning Vision-Language Models
CVPR 2025
FacLens: Transferable Probe for Foreseeing Non-Factuality in Fact-Seeking Question Answering of Large Language Models
EMNLP 2025
VLR-Driver: Large Vision-Language-Reasoning Models for Embodied Autonomous Driving
ICCV 2025
Reminiscence Attack on Residuals: Exploiting Approximate Machine Unlearning for Privacy
ICCV 2025
AutoGFM: Automated Graph Foundation Model with Adaptive Architecture Customization
ICML 2025
Self-supervised Masked Graph Autoencoder via Structure-aware Curriculum
ICML 2025
Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts
ICML 2025
A Selective Learning Method for Temporal Graph Continual Learning
ICML 2025
Graph Invariant Learning with Subgraph Co-mixup for Out-of-Distribution Generalization
AAAI 2024
Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference
AAAI 2024
CurBench: Curriculum Learning Benchmark
ICML 2024
Multimodal Graph Neural Architecture Search under Distribution Shifts
AAAI 2024
Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization
ICML 2024
A Generation-based Deductive Method for Math Word Problems
EMNLP 2023
Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts
NIPS 2023
RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL
AAAI 2023
Intent-aware Recommendation via Disentangled Graph Contrastive Learning
IJCAI 2023
AutoGT: Automated Graph Transformer Architecture Search
ICLR 2023
Curriculum Graph Machine Learning: A Survey
IJCAI 2023
Learning Invariant Graph Representations for Out-of-Distribution Generalization
NIPS 2022
Revisiting Injective Attacks on Recommender Systems
NIPS 2022
Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift
NIPS 2022
Disentangled Contrastive Learning on Graphs
NIPS 2021