Debate to Align: Reliable Entity Alignment through Two-Stage Multi-Agent Debate

ArXi:2604.13551v1 Announce Type: new Entity alignment (EA) aims to identify entities referring to the same real-world object across different knowledge graphs (KGs). Recent approaches based on large language models (LLMs) typically obtain entity embeddings through knowledge representation learning and use embedding similarity to identify an alignment-uncertain entity set. For each uncertain entity, a candidate entity set (CES) is then retrieved based on embedding similarity to subsequent alignment reasoning and decision making.