{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:HYVGEJVMLQZFHSXTTUCDLB4BPG","short_pith_number":"pith:HYVGEJVM","schema_version":"1.0","canonical_sha256":"3e2a6226ac5c3253caf39d0435878179b77f9a73fd624a8c942ae9b724f6abad","source":{"kind":"arxiv","id":"2606.02506","version":1},"attestation_state":"computed","paper":{"title":"Question-Aware Evidence Ledgers for Video Relational Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huadong Ma, Mengshi Qi, Yilin Ou","submitted_at":"2026-06-01T17:18:03Z","abstract_excerpt":"The VRR-QA challenge evaluates visual relational reasoning in videos, where answers often depend on implicit spatial relations, event boundaries, target identity, and dialogue context rather than a single salient frame. We present a test-time reasoning pipeline built around a strong GPT-5.5 video QA solver and a set of question-aware evidence ledgers. The initial solver answers each question from a uniform video representation, while routed ledgers are prompted to make the required targets, count units, reference frames, and temporal or spatial scope explicit for counting, spatial, endpoint, v"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.02506","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-01T17:18:03Z","cross_cats_sorted":[],"title_canon_sha256":"2bdab05017d898d2f13bf5c499ad387245b3dee6dc1a7b82a78754b69e2a24c5","abstract_canon_sha256":"9d7cf60334836048fe402b5a692f29c7964479974bedb53827f6592ecd31cc6f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T03:05:08.104335Z","signature_b64":"g29OWy3KQQVxDFz8OmxXdQ8+oDLUJ2KK45MT55rXHjOY+uPHYE1EC6HfEhVAZIA098rpAoGYF/SCR3fCaU+8BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e2a6226ac5c3253caf39d0435878179b77f9a73fd624a8c942ae9b724f6abad","last_reissued_at":"2026-06-02T03:05:08.103883Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T03:05:08.103883Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Question-Aware Evidence Ledgers for Video Relational Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Huadong Ma, Mengshi Qi, Yilin Ou","submitted_at":"2026-06-01T17:18:03Z","abstract_excerpt":"The VRR-QA challenge evaluates visual relational reasoning in videos, where answers often depend on implicit spatial relations, event boundaries, target identity, and dialogue context rather than a single salient frame. We present a test-time reasoning pipeline built around a strong GPT-5.5 video QA solver and a set of question-aware evidence ledgers. The initial solver answers each question from a uniform video representation, while routed ledgers are prompted to make the required targets, count units, reference frames, and temporal or spatial scope explicit for counting, spatial, endpoint, v"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.02506","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.02506/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.02506","created_at":"2026-06-02T03:05:08.103940+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.02506v1","created_at":"2026-06-02T03:05:08.103940+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.02506","created_at":"2026-06-02T03:05:08.103940+00:00"},{"alias_kind":"pith_short_12","alias_value":"HYVGEJVMLQZF","created_at":"2026-06-02T03:05:08.103940+00:00"},{"alias_kind":"pith_short_16","alias_value":"HYVGEJVMLQZFHSXT","created_at":"2026-06-02T03:05:08.103940+00:00"},{"alias_kind":"pith_short_8","alias_value":"HYVGEJVM","created_at":"2026-06-02T03:05:08.103940+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HYVGEJVMLQZFHSXTTUCDLB4BPG","json":"https://pith.science/pith/HYVGEJVMLQZFHSXTTUCDLB4BPG.json","graph_json":"https://pith.science/api/pith-number/HYVGEJVMLQZFHSXTTUCDLB4BPG/graph.json","events_json":"https://pith.science/api/pith-number/HYVGEJVMLQZFHSXTTUCDLB4BPG/events.json","paper":"https://pith.science/paper/HYVGEJVM"},"agent_actions":{"view_html":"https://pith.science/pith/HYVGEJVMLQZFHSXTTUCDLB4BPG","download_json":"https://pith.science/pith/HYVGEJVMLQZFHSXTTUCDLB4BPG.json","view_paper":"https://pith.science/paper/HYVGEJVM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.02506&json=true","fetch_graph":"https://pith.science/api/pith-number/HYVGEJVMLQZFHSXTTUCDLB4BPG/graph.json","fetch_events":"https://pith.science/api/pith-number/HYVGEJVMLQZFHSXTTUCDLB4BPG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HYVGEJVMLQZFHSXTTUCDLB4BPG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HYVGEJVMLQZFHSXTTUCDLB4BPG/action/storage_attestation","attest_author":"https://pith.science/pith/HYVGEJVMLQZFHSXTTUCDLB4BPG/action/author_attestation","sign_citation":"https://pith.science/pith/HYVGEJVMLQZFHSXTTUCDLB4BPG/action/citation_signature","submit_replication":"https://pith.science/pith/HYVGEJVMLQZFHSXTTUCDLB4BPG/action/replication_record"}},"created_at":"2026-06-02T03:05:08.103940+00:00","updated_at":"2026-06-02T03:05:08.103940+00:00"}