{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:AETIX3JLNXKKY7B4QANAEQFAA7","short_pith_number":"pith:AETIX3JL","schema_version":"1.0","canonical_sha256":"01268bed2b6dd4ac7c3c801a0240a007fb660e2ea701c6dedff29c8386155173","source":{"kind":"arxiv","id":"2607.14305","version":1},"attestation_state":"computed","paper":{"title":"DCVC-MB: Neural B-Frame Video Compression using State Space Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Arjun Arora, Arunkumar Mohananchettiar, Calvin-Khang Ta, Carlos Restrepo-Galeano, Jay Shingala, Kruthi Murali, Naga Akhil E S, Peng Yin, Sean McCarthy, Tong Shao","submitted_at":"2026-07-15T19:09:24Z","abstract_excerpt":"In this paper we propose DCVC-Mamba (DCVC-MB), a neural video codec framework for B-frame coding. Our approach incorporates an IBP frame strategy for low-delay B-frame coding, a spatio-temporal fusion model based on state-space models for bidirectional temporal prediction, and an entropy-aware skipping mechanism that selectively omits coding certain latents to reduce entropy coding times. In addition to our model contributions we also implement two inference-time strategies that enhance compression performance. Experimental evaluation shows that DCVC-MB compares favorably to existing NVCs and "},"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":"2607.14305","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-15T19:09:24Z","cross_cats_sorted":[],"title_canon_sha256":"6a33ea7d8de25e7a187656d0d8d89d99db081ffacc844b797786e9f6a554a8c0","abstract_canon_sha256":"10404a1283a7d27ba446c5066c418aafb66849e38c817a325b0a8e5b7a19f510"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-17T00:21:04.414538Z","signature_b64":"3e67QXnLAdiUUx2JO9c3NhQOZWCfIylWgWv1Giw+J0ijJwvK9Amy8EijQCJsd+NQ0rf4EnHm0UGk/QLJMNXnCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"01268bed2b6dd4ac7c3c801a0240a007fb660e2ea701c6dedff29c8386155173","last_reissued_at":"2026-07-17T00:21:04.413699Z","signature_status":"signed_v1","first_computed_at":"2026-07-17T00:21:04.413699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"DCVC-MB: Neural B-Frame Video Compression using State Space Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Arjun Arora, Arunkumar Mohananchettiar, Calvin-Khang Ta, Carlos Restrepo-Galeano, Jay Shingala, Kruthi Murali, Naga Akhil E S, Peng Yin, Sean McCarthy, Tong Shao","submitted_at":"2026-07-15T19:09:24Z","abstract_excerpt":"In this paper we propose DCVC-Mamba (DCVC-MB), a neural video codec framework for B-frame coding. Our approach incorporates an IBP frame strategy for low-delay B-frame coding, a spatio-temporal fusion model based on state-space models for bidirectional temporal prediction, and an entropy-aware skipping mechanism that selectively omits coding certain latents to reduce entropy coding times. In addition to our model contributions we also implement two inference-time strategies that enhance compression performance. Experimental evaluation shows that DCVC-MB compares favorably to existing NVCs and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.14305","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/2607.14305/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":"2607.14305","created_at":"2026-07-17T00:21:04.414134+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.14305v1","created_at":"2026-07-17T00:21:04.414134+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.14305","created_at":"2026-07-17T00:21:04.414134+00:00"},{"alias_kind":"pith_short_12","alias_value":"AETIX3JLNXKK","created_at":"2026-07-17T00:21:04.414134+00:00"},{"alias_kind":"pith_short_16","alias_value":"AETIX3JLNXKKY7B4","created_at":"2026-07-17T00:21:04.414134+00:00"},{"alias_kind":"pith_short_8","alias_value":"AETIX3JL","created_at":"2026-07-17T00:21:04.414134+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/AETIX3JLNXKKY7B4QANAEQFAA7","json":"https://pith.science/pith/AETIX3JLNXKKY7B4QANAEQFAA7.json","graph_json":"https://pith.science/api/pith-number/AETIX3JLNXKKY7B4QANAEQFAA7/graph.json","events_json":"https://pith.science/api/pith-number/AETIX3JLNXKKY7B4QANAEQFAA7/events.json","paper":"https://pith.science/paper/AETIX3JL"},"agent_actions":{"view_html":"https://pith.science/pith/AETIX3JLNXKKY7B4QANAEQFAA7","download_json":"https://pith.science/pith/AETIX3JLNXKKY7B4QANAEQFAA7.json","view_paper":"https://pith.science/paper/AETIX3JL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.14305&json=true","fetch_graph":"https://pith.science/api/pith-number/AETIX3JLNXKKY7B4QANAEQFAA7/graph.json","fetch_events":"https://pith.science/api/pith-number/AETIX3JLNXKKY7B4QANAEQFAA7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AETIX3JLNXKKY7B4QANAEQFAA7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AETIX3JLNXKKY7B4QANAEQFAA7/action/storage_attestation","attest_author":"https://pith.science/pith/AETIX3JLNXKKY7B4QANAEQFAA7/action/author_attestation","sign_citation":"https://pith.science/pith/AETIX3JLNXKKY7B4QANAEQFAA7/action/citation_signature","submit_replication":"https://pith.science/pith/AETIX3JLNXKKY7B4QANAEQFAA7/action/replication_record"}},"created_at":"2026-07-17T00:21:04.414134+00:00","updated_at":"2026-07-17T00:21:04.414134+00:00"}