{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:OZ2RAYOAWIZUHSO4NQKX2ZR2AD","short_pith_number":"pith:OZ2RAYOA","schema_version":"1.0","canonical_sha256":"76751061c0b23343c9dc6c157d663a00f2fbddc1347472c012edd7a9173cb780","source":{"kind":"arxiv","id":"2606.30557","version":1},"attestation_state":"computed","paper":{"title":"EcoVideo: Entropy-Orchestrated Video Generation Paradigm in Cloud-Edge Dynamics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guojie Luo, Hengyi Zhang, Jiayu Chen, Maoliang Li, Minyu Li, Xiang Chen, Xuanzhe Liu, Zihao Zheng","submitted_at":"2026-06-29T16:51:56Z","abstract_excerpt":"DiT video generation is latency-intensive due to iterative full-frame denoising, while prior cloud-edge methods largely rely on static inter-step decoupling and cannot leverage inter-frame similarity or adapt to system dynamics. We propose EcoVideo, an entropy-orchestrated framework for dynamic inter-frame decoupling: early-stage self-attention entropy provides a training-free estimate of frame-wise information density for frame selection; a cloud large model denoises sparse high-entropy keyframes; and an edge lightweight model reconstructs the remaining frames via motion-aware interpolation w"},"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":"2606.30557","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-29T16:51:56Z","cross_cats_sorted":[],"title_canon_sha256":"294bc4faa0e09cb0c95dd491f2f21c22a5568a4dc40cf2816737923571e8790a","abstract_canon_sha256":"eca4162ac255621ea0e2f3ebe9cf3516012dab3431b47b0915919e8b15add6fa"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T02:18:20.441552Z","signature_b64":"ub1kZa5OH0nJl/1RQ2CgJDft1cagfad2CBHlkmvhXee1DVQeJ6cHSWE+oOmw6OZxrTYkgQW/0yIJGKHyS+2nCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"76751061c0b23343c9dc6c157d663a00f2fbddc1347472c012edd7a9173cb780","last_reissued_at":"2026-06-30T02:18:20.441051Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T02:18:20.441051Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"EcoVideo: Entropy-Orchestrated Video Generation Paradigm in Cloud-Edge Dynamics","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guojie Luo, Hengyi Zhang, Jiayu Chen, Maoliang Li, Minyu Li, Xiang Chen, Xuanzhe Liu, Zihao Zheng","submitted_at":"2026-06-29T16:51:56Z","abstract_excerpt":"DiT video generation is latency-intensive due to iterative full-frame denoising, while prior cloud-edge methods largely rely on static inter-step decoupling and cannot leverage inter-frame similarity or adapt to system dynamics. We propose EcoVideo, an entropy-orchestrated framework for dynamic inter-frame decoupling: early-stage self-attention entropy provides a training-free estimate of frame-wise information density for frame selection; a cloud large model denoises sparse high-entropy keyframes; and an edge lightweight model reconstructs the remaining frames via motion-aware interpolation w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.30557","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/2606.30557/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":"2606.30557","created_at":"2026-06-30T02:18:20.441121+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.30557v1","created_at":"2026-06-30T02:18:20.441121+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.30557","created_at":"2026-06-30T02:18:20.441121+00:00"},{"alias_kind":"pith_short_12","alias_value":"OZ2RAYOAWIZU","created_at":"2026-06-30T02:18:20.441121+00:00"},{"alias_kind":"pith_short_16","alias_value":"OZ2RAYOAWIZUHSO4","created_at":"2026-06-30T02:18:20.441121+00:00"},{"alias_kind":"pith_short_8","alias_value":"OZ2RAYOA","created_at":"2026-06-30T02:18:20.441121+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/OZ2RAYOAWIZUHSO4NQKX2ZR2AD","json":"https://pith.science/pith/OZ2RAYOAWIZUHSO4NQKX2ZR2AD.json","graph_json":"https://pith.science/api/pith-number/OZ2RAYOAWIZUHSO4NQKX2ZR2AD/graph.json","events_json":"https://pith.science/api/pith-number/OZ2RAYOAWIZUHSO4NQKX2ZR2AD/events.json","paper":"https://pith.science/paper/OZ2RAYOA"},"agent_actions":{"view_html":"https://pith.science/pith/OZ2RAYOAWIZUHSO4NQKX2ZR2AD","download_json":"https://pith.science/pith/OZ2RAYOAWIZUHSO4NQKX2ZR2AD.json","view_paper":"https://pith.science/paper/OZ2RAYOA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.30557&json=true","fetch_graph":"https://pith.science/api/pith-number/OZ2RAYOAWIZUHSO4NQKX2ZR2AD/graph.json","fetch_events":"https://pith.science/api/pith-number/OZ2RAYOAWIZUHSO4NQKX2ZR2AD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OZ2RAYOAWIZUHSO4NQKX2ZR2AD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OZ2RAYOAWIZUHSO4NQKX2ZR2AD/action/storage_attestation","attest_author":"https://pith.science/pith/OZ2RAYOAWIZUHSO4NQKX2ZR2AD/action/author_attestation","sign_citation":"https://pith.science/pith/OZ2RAYOAWIZUHSO4NQKX2ZR2AD/action/citation_signature","submit_replication":"https://pith.science/pith/OZ2RAYOAWIZUHSO4NQKX2ZR2AD/action/replication_record"}},"created_at":"2026-06-30T02:18:20.441121+00:00","updated_at":"2026-06-30T02:18:20.441121+00:00"}