{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:VYHMVNRCDSPMIGTXKRCB5UD4IO","short_pith_number":"pith:VYHMVNRC","schema_version":"1.0","canonical_sha256":"ae0ecab6221c9ec41a7754441ed07c43a3305f79315c6b6ab8260bbd68905453","source":{"kind":"arxiv","id":"2606.06991","version":1},"attestation_state":"computed","paper":{"title":"Don't Pause: Streaming Video-Language Synchrony for Online Video Understanding","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Changsheng Xu, Kairui Zhang, Shengsheng Qian, Weiming Dong, Zhenyu Yang","submitted_at":"2026-06-05T07:29:20Z","abstract_excerpt":"Online Video Large Language Models (Video-LLMs) have advanced toward seamless human-AI interaction through frame-by-frame processing and proactive responding. However, a critical challenge remains in streaming scenarios: existing models typically pause video perception while generating responses, breaking real-time video-language synchrony and causing stutters. To address this, we introduce a novel paradigm for online video understanding: Streaming Video-Language Synchrony (SVLS), and present LyraV, a live streaming assistant built upon a hierarchical control framework with two core innovation"},"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":"2606.06991","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-05T07:29:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8634f2eafd8819a6e343a4a55a96c5d991910cf0e51f76fafcaa73c64519cf32","abstract_canon_sha256":"a5e7cb1bdd8bbf3f9e32e8f3945979195b17426b2a6d535f1569cbffa8e0a615"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-08T01:04:39.996118Z","signature_b64":"Tuh2911OXpls8lNFokZ/5ermz9R8eefd0TEmMePWjyc4zJEGhgXnj6Ly1wjs2c9EjX41Zi+OO10VngLl1IZvAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae0ecab6221c9ec41a7754441ed07c43a3305f79315c6b6ab8260bbd68905453","last_reissued_at":"2026-06-08T01:04:39.995161Z","signature_status":"signed_v1","first_computed_at":"2026-06-08T01:04:39.995161Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Don't Pause: Streaming Video-Language Synchrony for Online Video Understanding","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Changsheng Xu, Kairui Zhang, Shengsheng Qian, Weiming Dong, Zhenyu Yang","submitted_at":"2026-06-05T07:29:20Z","abstract_excerpt":"Online Video Large Language Models (Video-LLMs) have advanced toward seamless human-AI interaction through frame-by-frame processing and proactive responding. However, a critical challenge remains in streaming scenarios: existing models typically pause video perception while generating responses, breaking real-time video-language synchrony and causing stutters. To address this, we introduce a novel paradigm for online video understanding: Streaming Video-Language Synchrony (SVLS), and present LyraV, a live streaming assistant built upon a hierarchical control framework with two core innovation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.06991","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/2606.06991/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":"2606.06991","created_at":"2026-06-08T01:04:39.995339+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.06991v1","created_at":"2026-06-08T01:04:39.995339+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.06991","created_at":"2026-06-08T01:04:39.995339+00:00"},{"alias_kind":"pith_short_12","alias_value":"VYHMVNRCDSPM","created_at":"2026-06-08T01:04:39.995339+00:00"},{"alias_kind":"pith_short_16","alias_value":"VYHMVNRCDSPMIGTX","created_at":"2026-06-08T01:04:39.995339+00:00"},{"alias_kind":"pith_short_8","alias_value":"VYHMVNRC","created_at":"2026-06-08T01:04:39.995339+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/VYHMVNRCDSPMIGTXKRCB5UD4IO","json":"https://pith.science/pith/VYHMVNRCDSPMIGTXKRCB5UD4IO.json","graph_json":"https://pith.science/api/pith-number/VYHMVNRCDSPMIGTXKRCB5UD4IO/graph.json","events_json":"https://pith.science/api/pith-number/VYHMVNRCDSPMIGTXKRCB5UD4IO/events.json","paper":"https://pith.science/paper/VYHMVNRC"},"agent_actions":{"view_html":"https://pith.science/pith/VYHMVNRCDSPMIGTXKRCB5UD4IO","download_json":"https://pith.science/pith/VYHMVNRCDSPMIGTXKRCB5UD4IO.json","view_paper":"https://pith.science/paper/VYHMVNRC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.06991&json=true","fetch_graph":"https://pith.science/api/pith-number/VYHMVNRCDSPMIGTXKRCB5UD4IO/graph.json","fetch_events":"https://pith.science/api/pith-number/VYHMVNRCDSPMIGTXKRCB5UD4IO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VYHMVNRCDSPMIGTXKRCB5UD4IO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VYHMVNRCDSPMIGTXKRCB5UD4IO/action/storage_attestation","attest_author":"https://pith.science/pith/VYHMVNRCDSPMIGTXKRCB5UD4IO/action/author_attestation","sign_citation":"https://pith.science/pith/VYHMVNRCDSPMIGTXKRCB5UD4IO/action/citation_signature","submit_replication":"https://pith.science/pith/VYHMVNRCDSPMIGTXKRCB5UD4IO/action/replication_record"}},"created_at":"2026-06-08T01:04:39.995339+00:00","updated_at":"2026-06-08T01:04:39.995339+00:00"}