3 papers
cs.AI2026
Adversarial Yet Cooperative: Multi-Perspective Reasoning in Retrieved-Augmented Language Models
Can Xu, Lingyong Yan, Jiayi Wu +6
Recent advances in synergizing large reasoning models (LRMs) with retrieval-augmented generation (RAG) have shown promising results, yet two critical challenges remain: (1) reasoni…
cs.LG2025
Homophily-aware Heterogeneous Graph Contrastive Learning
Haosen Wang, Chenglong Shi, Can Xu +2
Heterogeneous graph pre-training (HGP) has demonstrated remarkable performance across various domains. However, the issue of heterophily in real-world heterogeneous graphs (HGs) ha…
cs.LG2024
Improving Graph Out-of-distribution Generalization Beyond Causality
Can Xu, Yao Cheng, Jianxiang Yu +4
Existing methods for graph out-of-distribution (OOD) generalization primarily rely on empirical studies on synthetic datasets. Such approaches tend to overemphasize the causal rela…