{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QXWAYTG6OHE6L7RL3B3SXB5FIL","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"2f2a09bfcdfef07d12e3d5736a8ec8780517c1da155928f08442a3b4bbaf7f21","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-05T17:59:54Z","title_canon_sha256":"4cf7095ea190533ec16a71013708f841fb3dedfb654239e6c996185f01295d07"},"schema_version":"1.0","source":{"id":"2506.05343","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05343","created_at":"2026-07-05T11:19:53Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05343v2","created_at":"2026-07-05T11:19:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05343","created_at":"2026-07-05T11:19:53Z"},{"alias_kind":"pith_short_12","alias_value":"QXWAYTG6OHE6","created_at":"2026-07-05T11:19:53Z"},{"alias_kind":"pith_short_16","alias_value":"QXWAYTG6OHE6L7RL","created_at":"2026-07-05T11:19:53Z"},{"alias_kind":"pith_short_8","alias_value":"QXWAYTG6","created_at":"2026-07-05T11:19:53Z"}],"graph_snapshots":[{"event_id":"sha256:cdc0ecb41d4145e769fc5182052d20c2ae6ace801b49703772dc00b495dbfae3","target":"graph","created_at":"2026-07-05T11:19:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2506.05343/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in video generation demand increasingly efficient training recipes to mitigate escalating computational costs. In this report, we present ContentV, an 8B-parameter text-to-video model that achieves state-of-the-art performance (85.14 on VBench) after training on 256 x 64GB Neural Processing Units (NPUs) for merely four weeks. ContentV generates diverse, high-quality videos across multiple resolutions and durations from text prompts, enabled by three key innovations: (1) A minimalist architecture that maximizes reuse of pre-trained image generation models for video generation; (","authors_text":"Boyuan Liu, Chao Feng, Jiangchuan Wei, Jiao Ran, Mingyu Guo, Qi Wu, Renjie Chen, Ruoyu Feng, Shiyue Yan, Wenfeng Lin, Yichen Zhang, Yimeng Zhou, Zuotao Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-05T17:59:54Z","title":"ContentV: Efficient Training of Video Generation Models with Limited Compute"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05343","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:c26bfeeb1f0724ac348450bac8020a4cc31592da2f191845b84b7918b10fcf62","target":"record","created_at":"2026-07-05T11:19:53Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"2f2a09bfcdfef07d12e3d5736a8ec8780517c1da155928f08442a3b4bbaf7f21","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-05T17:59:54Z","title_canon_sha256":"4cf7095ea190533ec16a71013708f841fb3dedfb654239e6c996185f01295d07"},"schema_version":"1.0","source":{"id":"2506.05343","kind":"arxiv","version":2}},"canonical_sha256":"85ec0c4cde71c9e5fe2bd8772b87a542f08e5b94014e78d6fc344555e2ae3bd8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"85ec0c4cde71c9e5fe2bd8772b87a542f08e5b94014e78d6fc344555e2ae3bd8","first_computed_at":"2026-07-05T11:19:53.527034Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:19:53.527034Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bZ7295pZoAb3hj9m1Zt9NLAQanDA9BWjZLKALKibJInN5j3jql1ItZqgS+unRWhku9POXN7qSC8Jld/7sUc8CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:19:53.527590Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.05343","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c26bfeeb1f0724ac348450bac8020a4cc31592da2f191845b84b7918b10fcf62","sha256:cdc0ecb41d4145e769fc5182052d20c2ae6ace801b49703772dc00b495dbfae3"],"state_sha256":"ea819e48ecd4356721b25e6a70b1fc2e7b6ed487a8b99afe1cfbf30175b17e90"}