{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:UKCV67CIS4JAHSACVXT5YHANOW","short_pith_number":"pith:UKCV67CI","schema_version":"1.0","canonical_sha256":"a2855f7c48971203c802ade7dc1c0d75af28b3113966eac2f7be6f055e411c9c","source":{"kind":"arxiv","id":"2508.13547","version":1},"attestation_state":"computed","paper":{"title":"A Lightweight Dual-Mode Optimization for Generative Face Video Coding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Bolin Chen, Ru-Ling Liao, Shanzhi Yin, Shiqi Wang, Yan Ye, Zihan Zhang","submitted_at":"2025-08-19T06:09:28Z","abstract_excerpt":"Generative Face Video Coding (GFVC) achieves superior rate-distortion performance by leveraging the strong inference capabilities of deep generative models. However, its practical deployment is hindered by large model parameters and high computational costs. To address this, we propose a lightweight GFVC framework that introduces dual-mode optimization -- combining architectural redesign and operational refinement -- to reduce complexity whilst preserving reconstruction quality. Architecturally, we replace traditional 3 x 3 convolutions with slimmer and more efficient layers, reducing complexi"},"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":"2508.13547","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-08-19T06:09:28Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"38e43cd245ec5f59a3d79b8fa25f4709ee876364d96abb8fa7628d0ed36b8d91","abstract_canon_sha256":"aaa1b30d7302ecab3a8706f79b05632a90b94c68aa8175d3c78c82ba868f7200"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:56:06.717179Z","signature_b64":"3grrdyQb+CEQJR88lrTE3bhIZAAQmYg+WA0MsOtXb1X0tAR+dBi62WrI+dmOI6gKWs/2VmNTOLsU1BEzeKntCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a2855f7c48971203c802ade7dc1c0d75af28b3113966eac2f7be6f055e411c9c","last_reissued_at":"2026-07-05T11:56:06.716701Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:56:06.716701Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Lightweight Dual-Mode Optimization for Generative Face Video Coding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Bolin Chen, Ru-Ling Liao, Shanzhi Yin, Shiqi Wang, Yan Ye, Zihan Zhang","submitted_at":"2025-08-19T06:09:28Z","abstract_excerpt":"Generative Face Video Coding (GFVC) achieves superior rate-distortion performance by leveraging the strong inference capabilities of deep generative models. However, its practical deployment is hindered by large model parameters and high computational costs. To address this, we propose a lightweight GFVC framework that introduces dual-mode optimization -- combining architectural redesign and operational refinement -- to reduce complexity whilst preserving reconstruction quality. Architecturally, we replace traditional 3 x 3 convolutions with slimmer and more efficient layers, reducing complexi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.13547","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/2508.13547/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":"2508.13547","created_at":"2026-07-05T11:56:06.716777+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.13547v1","created_at":"2026-07-05T11:56:06.716777+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.13547","created_at":"2026-07-05T11:56:06.716777+00:00"},{"alias_kind":"pith_short_12","alias_value":"UKCV67CIS4JA","created_at":"2026-07-05T11:56:06.716777+00:00"},{"alias_kind":"pith_short_16","alias_value":"UKCV67CIS4JAHSAC","created_at":"2026-07-05T11:56:06.716777+00:00"},{"alias_kind":"pith_short_8","alias_value":"UKCV67CI","created_at":"2026-07-05T11:56:06.716777+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/UKCV67CIS4JAHSACVXT5YHANOW","json":"https://pith.science/pith/UKCV67CIS4JAHSACVXT5YHANOW.json","graph_json":"https://pith.science/api/pith-number/UKCV67CIS4JAHSACVXT5YHANOW/graph.json","events_json":"https://pith.science/api/pith-number/UKCV67CIS4JAHSACVXT5YHANOW/events.json","paper":"https://pith.science/paper/UKCV67CI"},"agent_actions":{"view_html":"https://pith.science/pith/UKCV67CIS4JAHSACVXT5YHANOW","download_json":"https://pith.science/pith/UKCV67CIS4JAHSACVXT5YHANOW.json","view_paper":"https://pith.science/paper/UKCV67CI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.13547&json=true","fetch_graph":"https://pith.science/api/pith-number/UKCV67CIS4JAHSACVXT5YHANOW/graph.json","fetch_events":"https://pith.science/api/pith-number/UKCV67CIS4JAHSACVXT5YHANOW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UKCV67CIS4JAHSACVXT5YHANOW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UKCV67CIS4JAHSACVXT5YHANOW/action/storage_attestation","attest_author":"https://pith.science/pith/UKCV67CIS4JAHSACVXT5YHANOW/action/author_attestation","sign_citation":"https://pith.science/pith/UKCV67CIS4JAHSACVXT5YHANOW/action/citation_signature","submit_replication":"https://pith.science/pith/UKCV67CIS4JAHSACVXT5YHANOW/action/replication_record"}},"created_at":"2026-07-05T11:56:06.716777+00:00","updated_at":"2026-07-05T11:56:06.716777+00:00"}