pith:5F2FTTYQ
STEM: Structure-Tracing Evidence Mining for Knowledge Graphs-Driven Retrieval-Augmented Generation
STEM reframes multi-hop reasoning over knowledge graphs as schema-guided graph search to raise both accuracy and evidence completeness.
arxiv:2604.22282 v2 · 2026-04-24 · cs.CL
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\pithnumber{5F2FTTYQ7VROHAVDZWKV5FKCML}
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Record completeness
Claims
STEM significantly improves both the accuracy and evidence completeness of multi-hop reasoning graph retrieval, and achieves State-of-the-Art performance on multiple multi-hop benchmarks.
That the Semantic-to-Structural Projection pipeline can effectively leverage KG structural priors to decompose queries into atomic relational assertions and construct an adaptive query schema graph without significant semantic mismatch or loss of query intent.
STEM is a new framework for multi-hop KGQA that projects queries to adaptive schema graphs and uses Triple-GNN guidance to retrieve more accurate and complete evidence subgraphs, claiming SOTA results.
Receipt and verification
| First computed | 2026-05-20T00:04:32.570612Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
e97459cf10fd62e382a3cd955e954262c48793c0235359cbfed31466584c1223
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/5F2FTTYQ7VROHAVDZWKV5FKCML \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: e97459cf10fd62e382a3cd955e954262c48793c0235359cbfed31466584c1223
Canonical record JSON
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