{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XKSBDS2Q2NENICCQTYNRR44MTA","short_pith_number":"pith:XKSBDS2Q","canonical_record":{"source":{"id":"2502.01776","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T19:29:16Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1a7fb0ba3bd9e826058c8279ab6a528606ab53f95042dad7a40ab092a9f302e7","abstract_canon_sha256":"8e64a1460cfc54b551043a619040800247176d0c2dc0e11122a79d266b053ed6"},"schema_version":"1.0"},"canonical_sha256":"baa411cb50d348d408509e1b18f38c98266abd7882b43d335cc0f561e327f3da","source":{"kind":"arxiv","id":"2502.01776","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.01776","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"arxiv_version","alias_value":"2502.01776v2","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.01776","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"pith_short_12","alias_value":"XKSBDS2Q2NEN","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"pith_short_16","alias_value":"XKSBDS2Q2NENICCQ","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"pith_short_8","alias_value":"XKSBDS2Q","created_at":"2026-07-05T10:54:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XKSBDS2Q2NENICCQTYNRR44MTA","target":"record","payload":{"canonical_record":{"source":{"id":"2502.01776","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T19:29:16Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1a7fb0ba3bd9e826058c8279ab6a528606ab53f95042dad7a40ab092a9f302e7","abstract_canon_sha256":"8e64a1460cfc54b551043a619040800247176d0c2dc0e11122a79d266b053ed6"},"schema_version":"1.0"},"canonical_sha256":"baa411cb50d348d408509e1b18f38c98266abd7882b43d335cc0f561e327f3da","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:54:42.702093Z","signature_b64":"clJRPYcVMBpTMTh58FxIZCj7yPq4iUnXmsVERYIOZNfDDF7UVQf4opcTGO08ljsYU4x+4T4Pz4MsZ+0waNxaBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"baa411cb50d348d408509e1b18f38c98266abd7882b43d335cc0f561e327f3da","last_reissued_at":"2026-07-05T10:54:42.701573Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:54:42.701573Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.01776","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:54:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9RSVl7lxx3sUYWPAHwNB5zWa6BNUYJSi+6oyxWKdtTvvSodsHdkgTbpyKkuA4mfgp4Ww8e3AB4F7rdrqBvmqBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T15:47:01.424795Z"},"content_sha256":"eb09ebbcae771d6e9b712a4689c540f986da605465510a278fe5904a6b355b34","schema_version":"1.0","event_id":"sha256:eb09ebbcae771d6e9b712a4689c540f986da605465510a278fe5904a6b355b34"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XKSBDS2Q2NENICCQTYNRR44MTA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Chenfeng Xu, Dacheng Li, Han Cai, Haocheng Xi, Ion Stoica, Jianfei Chen, Jintao Zhang, Kurt Keutzer, Muyang Li, Shuo Yang, Song Han, Xiuyu Li, Yilong Zhao, Yujun Lin","submitted_at":"2025-02-03T19:29:16Z","abstract_excerpt":"Diffusion Transformers (DiTs) dominate video generation but their high computational cost severely limits real-world applicability, usually requiring tens of minutes to generate a few seconds of video even on high-performance GPUs. This inefficiency primarily arises from the quadratic computational complexity of 3D Full Attention with respect to the context length. In this paper, we propose a training-free framework termed Sparse VideoGen (SVG) that leverages the inherent sparsity in 3D Full Attention to boost inference efficiency. We reveal that the attention heads can be dynamically classifi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.01776","kind":"arxiv","version":2},"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/2502.01776/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:54:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a+R6hKyW2W73RVHjFdSByhmJTyNzu+zkRlYqvpeUBOvrdz3n1CtIi+0sgkuolG3Dz6yPWfnA7AMapHp5wrDBBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T15:47:01.425277Z"},"content_sha256":"1d441ed00f1acd87f5047cc89e3386eec6518d58dc35ca2d96022c53f29b105c","schema_version":"1.0","event_id":"sha256:1d441ed00f1acd87f5047cc89e3386eec6518d58dc35ca2d96022c53f29b105c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XKSBDS2Q2NENICCQTYNRR44MTA/bundle.json","state_url":"https://pith.science/pith/XKSBDS2Q2NENICCQTYNRR44MTA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XKSBDS2Q2NENICCQTYNRR44MTA/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-01T15:47:01Z","links":{"resolver":"https://pith.science/pith/XKSBDS2Q2NENICCQTYNRR44MTA","bundle":"https://pith.science/pith/XKSBDS2Q2NENICCQTYNRR44MTA/bundle.json","state":"https://pith.science/pith/XKSBDS2Q2NENICCQTYNRR44MTA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XKSBDS2Q2NENICCQTYNRR44MTA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XKSBDS2Q2NENICCQTYNRR44MTA","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":"8e64a1460cfc54b551043a619040800247176d0c2dc0e11122a79d266b053ed6","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T19:29:16Z","title_canon_sha256":"1a7fb0ba3bd9e826058c8279ab6a528606ab53f95042dad7a40ab092a9f302e7"},"schema_version":"1.0","source":{"id":"2502.01776","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.01776","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"arxiv_version","alias_value":"2502.01776v2","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.01776","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"pith_short_12","alias_value":"XKSBDS2Q2NEN","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"pith_short_16","alias_value":"XKSBDS2Q2NENICCQ","created_at":"2026-07-05T10:54:42Z"},{"alias_kind":"pith_short_8","alias_value":"XKSBDS2Q","created_at":"2026-07-05T10:54:42Z"}],"graph_snapshots":[{"event_id":"sha256:1d441ed00f1acd87f5047cc89e3386eec6518d58dc35ca2d96022c53f29b105c","target":"graph","created_at":"2026-07-05T10:54:42Z","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/2502.01776/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion Transformers (DiTs) dominate video generation but their high computational cost severely limits real-world applicability, usually requiring tens of minutes to generate a few seconds of video even on high-performance GPUs. This inefficiency primarily arises from the quadratic computational complexity of 3D Full Attention with respect to the context length. In this paper, we propose a training-free framework termed Sparse VideoGen (SVG) that leverages the inherent sparsity in 3D Full Attention to boost inference efficiency. We reveal that the attention heads can be dynamically classifi","authors_text":"Chenfeng Xu, Dacheng Li, Han Cai, Haocheng Xi, Ion Stoica, Jianfei Chen, Jintao Zhang, Kurt Keutzer, Muyang Li, Shuo Yang, Song Han, Xiuyu Li, Yilong Zhao, Yujun Lin","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T19:29:16Z","title":"Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.01776","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:eb09ebbcae771d6e9b712a4689c540f986da605465510a278fe5904a6b355b34","target":"record","created_at":"2026-07-05T10:54:42Z","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":"8e64a1460cfc54b551043a619040800247176d0c2dc0e11122a79d266b053ed6","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-03T19:29:16Z","title_canon_sha256":"1a7fb0ba3bd9e826058c8279ab6a528606ab53f95042dad7a40ab092a9f302e7"},"schema_version":"1.0","source":{"id":"2502.01776","kind":"arxiv","version":2}},"canonical_sha256":"baa411cb50d348d408509e1b18f38c98266abd7882b43d335cc0f561e327f3da","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"baa411cb50d348d408509e1b18f38c98266abd7882b43d335cc0f561e327f3da","first_computed_at":"2026-07-05T10:54:42.701573Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:54:42.701573Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"clJRPYcVMBpTMTh58FxIZCj7yPq4iUnXmsVERYIOZNfDDF7UVQf4opcTGO08ljsYU4x+4T4Pz4MsZ+0waNxaBA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:54:42.702093Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.01776","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb09ebbcae771d6e9b712a4689c540f986da605465510a278fe5904a6b355b34","sha256:1d441ed00f1acd87f5047cc89e3386eec6518d58dc35ca2d96022c53f29b105c"],"state_sha256":"21490052790515bba2a896d35eeb15d6e7a3afb97315aeb3bb6fca307ff91d16"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PvwNSdVlrVQmbyPp9ixNWzvvTTH4A8xunT/N6kHIFYMtkg9ewPEsk59i3x3Oh+raBV+/DZNhqxjVeImR1ZH/Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T15:47:01.428424Z","bundle_sha256":"23f0cd9c1ad2afc171b634ef2deb6e926c6215a205977eb8331deab96798679e"}}