Skill-Conditioned Visual Geolocation for Vision-Language explores A training-free framework uses an evolving skill graph to improve vision-language geolocation and enable autonomous self-evolution.. Commercial viability score: 7/10 in Vision-Language.
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This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Freshness
Canonical route: /paper/skill-conditioned-visual-geolocation-for-vision-language
Proof data is outside the preferred freshness window.
Proof Quality
One canonical proof ledger now drives the badge, counts, indexing, and commercialization gating.
Commercialization rails stay hidden until proof clears: proof_status, references_count.
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Agent Handoff
Canonical ID skill-conditioned-visual-geolocation-for-vision-language | Route /paper/skill-conditioned-visual-geolocation-for-vision-language
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/skill-conditioned-visual-geolocation-for-vision-languageMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.09025"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "Skill-Conditioned Visual Geolocation for Vision-Language",
"normalized_query": "2604.09025",
"route": "/paper/skill-conditioned-visual-geolocation-for-vision-language",
"paper_ref": "skill-conditioned-visual-geolocation-for-vision-language",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
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Dimensions overall score 7.0
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