EgoEsportsQA: An Egocentric Video Benchmark for Perception and Reasoning in Esports explores A new benchmark and dataset for evaluating Video-LLMs in high-velocity esports environments, revealing significant performance gaps and guiding future development.. Commercial viability score: 7/10 in Video LLMs.
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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/egoesportsqa-an-egocentric-video-benchmark-for-perception-and-reasoning-in-esports
Verification is still converging across references, source coverage, and proof checks.
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.
Search indexing stays off until proof clears: proof_status, references_count.
Agent Handoff
Canonical ID egoesportsqa-an-egocentric-video-benchmark-for-perception-and-reasoning-in-esports | Route /paper/egoesportsqa-an-egocentric-video-benchmark-for-perception-and-reasoning-in-esports
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/egoesportsqa-an-egocentric-video-benchmark-for-perception-and-reasoning-in-esportsMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.12320"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "EgoEsportsQA: An Egocentric Video Benchmark for Perception and Reasoning in Esports",
"normalized_query": "2604.12320",
"route": "/paper/egoesportsqa-an-egocentric-video-benchmark-for-perception-and-reasoning-in-esports",
"paper_ref": "egoesportsqa-an-egocentric-video-benchmark-for-perception-and-reasoning-in-esports",
"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.
Research neighborhood
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Preparing verified analysis
Dimensions overall score 7.0
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