Papers by Dongzhuoran Zhou

2 papers
What Breaks Knowledge Graph based RAG? Benchmarking and Empirical Insights into Reasoning under Incomplete Knowledge (2026.eacl-long)

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Challenge: Existing evaluation metrics and lenient answer matching criteria obscure meaningful comparisons.
Approach: They propose a general method for constructing benchmarks and a method to assess KG-RAG methods under incomplete knowledge.
Outcome: The proposed method systematically assesses KG-RAG methods under incomplete knowledge.
SCAIR: Schema-Conditioned Agentic Iterative Reasoning for Enterprise Knowledge Graphs (2026.acl-industry)

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Challenge: Existing agentic approaches for Knowledge Graph-based Retrieval-Augmented Generation fail to generalize to real-world enterprise Knowledge graphs (KGs) dense, schema-driven, and operationally constrained, requiring a training-free framework.
Approach: They propose a training-free framework that integrates structured planning with controlled iterative reasoning by injecting schema-conditioned structural priors and enforcing schemas during multi-hop reasoning.
Outcome: The proposed framework significantly improves on a real-world enterprise-oriented benchmark constructed from a Configuration Management DataBase (CMDB).

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