5 papers
Harnessing Structural Context for Entity Alignment Foundation Models
Xingyu Chen, Yuanning Cui, Zequn Sun +1
Entity alignment (EA) aims to identify equivalent entities across heterogeneous knowledge graphs (KGs) and is a key component of knowledge fusion and cross-KG reasoning. The recent…
Breaking the Reasoning Horizon in Entity Alignment Foundation Models
Yuanning Cui, Zequn Sun, Wei Hu +2
Entity alignment (EA) is critical for knowledge graph (KG) fusion. Existing EA models lack transferability and are incapable of aligning unseen KGs without retraining. While using…
SafeThinker: Reasoning about Risk to Deepen Safety Beyond Shallow Alignment
Xianya Fang, Xianying Luo, Yadong Wang +8
Despite the intrinsic risk-awareness of Large Language Models (LLMs), current defenses often result in shallow safety alignment, rendering models vulnerable to disguised attacks (e…
KGFR: A Foundation Retriever for Generalized Knowledge Graph Question Answering
Yuanning Cui, Zequn Sun, Wei Hu +1
Large language models (LLMs) excel at reasoning but struggle with knowledge-intensive questions due to limited context and parametric knowledge. However, existing methods that rely…
A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning
Yuanning Cui, Zequn Sun, Wei Hu
Extensive knowledge graphs (KGs) have been constructed to facilitate knowledge-driven tasks across various scenarios. However, existing work usually develops separate reasoning mod…