STEM reframes multi-hop KGQA as schema-guided graph search with semantic-to-structural projection and Triple-GNN guidance, claiming SOTA accuracy and evidence completeness on multi-hop benchmarks.
B.2 Implementation Details STEM involves three LLM-based modules: SGDA, SAGB, and the LLM reasoning model
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
STEM: Structure-Tracing Evidence Mining for Knowledge Graphs-Driven Retrieval-Augmented Generation
STEM reframes multi-hop KGQA as schema-guided graph search with semantic-to-structural projection and Triple-GNN guidance, claiming SOTA accuracy and evidence completeness on multi-hop benchmarks.