pith:6PLKBFMQ
Geodesic Semantic Search: Cartographic Navigation of Citation Graphs with Learned Local Riemannian Maps
Learning node-specific Riemannian metrics on citation graphs turns direct similarity search into geodesic navigation that improves recall.
arxiv:2602.23665 v5 · 2026-02-27 · cs.IR · cs.LG · cs.SI
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\usepackage{pith}
\pithnumber{6PLKBFMQLD6PSTPW574NZ7XMHQ}
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Record completeness
Claims
On citation prediction benchmarks with 169K arXiv papers, GSS achieves 23% relative improvement in Recall@20 over SPECTER+FAISS baselines.
That the learned local Riemannian metrics meaningfully capture semantic relationships in the citation graph rather than merely fitting training patterns.
GSS learns per-node low-rank Riemannian metrics on citation graphs and retrieves via geodesic distances, yielding 23% higher Recall@20 than SPECTER+FAISS on 169K arXiv papers.
Receipt and verification
| First computed | 2026-06-05T01:15:22.468076Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
f3d6a0959058fcf94df6eff8dcfeec3c26ef62a4b7e3ff10a5faccc24450fa72
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/6PLKBFMQLD6PSTPW574NZ7XMHQ \
| 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: f3d6a0959058fcf94df6eff8dcfeec3c26ef62a4b7e3ff10a5faccc24450fa72
Canonical record JSON
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],
"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.IR",
"submitted_at": "2026-02-27T04:17:41Z",
"title_canon_sha256": "28edb9a09a6bd0ec50bb14e10a5cee236ff4d72921e9d3db11a191a08b175d53"
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"kind": "arxiv",
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