Yongqiang Chen
20 papers · 2022–2026 · 6 conferences · across top CS/AI conferences
Achievements
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Conferences
NIPS (8)
ICLR (5)
ICML (3)
AAAI (2)
ACL (1)
EMNLP (1)
Top co-authors
Keywords
domain generalization
(4)
out-of-distribution generalization
(3)
causal inference
(3)
causal model
(2)
representation learning
(2)
large language model
(2)
graph neural network
(2)
spurious correlation
(2)
invariant learning
(2)
graph classification
(1)
machine unlearning
(1)
preference optimization
(1)
graph representation
(1)
causal discovery
(1)
chain-of-thought reasoning
(1)
shape matching
(1)
graph representation learning
(1)
mutual information
(1)
hierarchical representation
(1)
attention mechanism
(1)
Papers
CiPO: Counterfactual Unlearning for Large Reasoning Models through Iterative Preference Optimization
ACL 2026
Retrieval-Augmented Generation with Hierarchical Knowledge
EMNLP 2025
Eliciting Causal Abilities in Large Language Models for Reasoning Tasks
AAAI 2025
Learning Graph Invariance by Harnessing Spuriosity
ICLR 2025
BrainOOD: Out-of-distribution Generalizable Brain Network Analysis
ICLR 2025
Hierarchical Graph Tokenization for Molecule-Language Alignment
ICML 2025
On the Comparison between Multi-modal and Single-modal Contrastive Learning
NIPS 2024
A Sober Look at the Robustness of CLIPs to Spurious Features
NIPS 2024
Enhancing Evolving Domain Generalization through Dynamic Latent Representations
AAAI 2024
How Interpretable Are Interpretable Graph Neural Networks?
ICML 2024
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations
ICLR 2024
Empowering Graph Invariance Learning with Deep Spurious Infomax
ICML 2024
HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection
NIPS 2024
Discovery of the Hidden World with Large Language Models
NIPS 2024
Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
NIPS 2023
Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization
ICLR 2023
Understanding and Improving Feature Learning for Out-of-Distribution Generalization
NIPS 2023
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
NIPS 2022
Exact Shape Correspondence via 2D graph convolution
NIPS 2022
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
ICLR 2022