{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:YPA2LSTGEEW2V7IFB3WOXQ3R7M","short_pith_number":"pith:YPA2LSTG","canonical_record":{"source":{"id":"2109.01696","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-03T18:27:52Z","cross_cats_sorted":["cs.LG","eess.IV"],"title_canon_sha256":"e5e86a85b012a6c90c569fc3a21ff32be80b46e869135b89fbb4796bac9a108f","abstract_canon_sha256":"8ef2ace877d2da0564b481ea11993d1500484fd655548c672f59090aff591fe3"},"schema_version":"1.0"},"canonical_sha256":"c3c1a5ca66212daafd050eecebc371fb0a5a08982df702d319bc2a5ab8737d63","source":{"kind":"arxiv","id":"2109.01696","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.01696","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"arxiv_version","alias_value":"2109.01696v1","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.01696","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"pith_short_12","alias_value":"YPA2LSTGEEW2","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"pith_short_16","alias_value":"YPA2LSTGEEW2V7IF","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"pith_short_8","alias_value":"YPA2LSTG","created_at":"2026-07-05T03:11:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:YPA2LSTGEEW2V7IFB3WOXQ3R7M","target":"record","payload":{"canonical_record":{"source":{"id":"2109.01696","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-03T18:27:52Z","cross_cats_sorted":["cs.LG","eess.IV"],"title_canon_sha256":"e5e86a85b012a6c90c569fc3a21ff32be80b46e869135b89fbb4796bac9a108f","abstract_canon_sha256":"8ef2ace877d2da0564b481ea11993d1500484fd655548c672f59090aff591fe3"},"schema_version":"1.0"},"canonical_sha256":"c3c1a5ca66212daafd050eecebc371fb0a5a08982df702d319bc2a5ab8737d63","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:11:33.826153Z","signature_b64":"2ZQBsBNScvChNetFA/1YDrIwGDErejwFCOIK1CCLwMNrjQXBfOSxuiuN8I61ashzi8Krhx4r6hJN7hdZZG+fCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c3c1a5ca66212daafd050eecebc371fb0a5a08982df702d319bc2a5ab8737d63","last_reissued_at":"2026-07-05T03:11:33.825540Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:11:33.825540Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2109.01696","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:11:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3ZRu3q15/RAaeEQ1NxDzlz6YBh4JzfYmd5nZef3Bg4mfJBxpZQe3PcGZW2rnd6fZLnx3nUS2KZNnYKCiJhThBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T04:32:24.286178Z"},"content_sha256":"e4cdf2f43931b9c7c432872963702029eafdd223b249ec56b94cebdd5254f309","schema_version":"1.0","event_id":"sha256:e4cdf2f43931b9c7c432872963702029eafdd223b249ec56b94cebdd5254f309"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:YPA2LSTGEEW2V7IFB3WOXQ3R7M","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisiting 3D ResNets for Video Recognition","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","eess.IV"],"primary_cat":"cs.CV","authors_text":"Irwan Bello, Jing Li, Rui Qian, Xianzhi Du, Yeqing Li, Yin Cui","submitted_at":"2021-09-03T18:27:52Z","abstract_excerpt":"A recent work from Bello shows that training and scaling strategies may be more significant than model architectures for visual recognition. This short note studies effective training and scaling strategies for video recognition models. We propose a simple scaling strategy for 3D ResNets, in combination with improved training strategies and minor architectural changes. The resulting models, termed 3D ResNet-RS, attain competitive performance of 81.0 on Kinetics-400 and 83.8 on Kinetics-600 without pre-training. When pre-trained on a large Web Video Text dataset, our best model achieves 83.5 an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.01696","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/2109.01696/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":"2026-07-05T03:11:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nPdXq+jNX2UkM2mTq4jlZj2z20rP7buhExC5XTaOyC3p60Gut8GcmzFT1BdDBDHQnkRu9hpjCtVJ/eYemTebAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T04:32:24.286580Z"},"content_sha256":"bee6e3ff3bbfdc080f2c4b9d61b16753b341e3ce801255c391f8190e333a9cf1","schema_version":"1.0","event_id":"sha256:bee6e3ff3bbfdc080f2c4b9d61b16753b341e3ce801255c391f8190e333a9cf1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YPA2LSTGEEW2V7IFB3WOXQ3R7M/bundle.json","state_url":"https://pith.science/pith/YPA2LSTGEEW2V7IFB3WOXQ3R7M/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YPA2LSTGEEW2V7IFB3WOXQ3R7M/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":"2026-08-07T04:32:24Z","links":{"resolver":"https://pith.science/pith/YPA2LSTGEEW2V7IFB3WOXQ3R7M","bundle":"https://pith.science/pith/YPA2LSTGEEW2V7IFB3WOXQ3R7M/bundle.json","state":"https://pith.science/pith/YPA2LSTGEEW2V7IFB3WOXQ3R7M/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YPA2LSTGEEW2V7IFB3WOXQ3R7M/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:YPA2LSTGEEW2V7IFB3WOXQ3R7M","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":"8ef2ace877d2da0564b481ea11993d1500484fd655548c672f59090aff591fe3","cross_cats_sorted":["cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-03T18:27:52Z","title_canon_sha256":"e5e86a85b012a6c90c569fc3a21ff32be80b46e869135b89fbb4796bac9a108f"},"schema_version":"1.0","source":{"id":"2109.01696","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.01696","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"arxiv_version","alias_value":"2109.01696v1","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.01696","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"pith_short_12","alias_value":"YPA2LSTGEEW2","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"pith_short_16","alias_value":"YPA2LSTGEEW2V7IF","created_at":"2026-07-05T03:11:33Z"},{"alias_kind":"pith_short_8","alias_value":"YPA2LSTG","created_at":"2026-07-05T03:11:33Z"}],"graph_snapshots":[{"event_id":"sha256:bee6e3ff3bbfdc080f2c4b9d61b16753b341e3ce801255c391f8190e333a9cf1","target":"graph","created_at":"2026-07-05T03:11:33Z","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/2109.01696/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A recent work from Bello shows that training and scaling strategies may be more significant than model architectures for visual recognition. This short note studies effective training and scaling strategies for video recognition models. We propose a simple scaling strategy for 3D ResNets, in combination with improved training strategies and minor architectural changes. The resulting models, termed 3D ResNet-RS, attain competitive performance of 81.0 on Kinetics-400 and 83.8 on Kinetics-600 without pre-training. When pre-trained on a large Web Video Text dataset, our best model achieves 83.5 an","authors_text":"Irwan Bello, Jing Li, Rui Qian, Xianzhi Du, Yeqing Li, Yin Cui","cross_cats":["cs.LG","eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-03T18:27:52Z","title":"Revisiting 3D ResNets for Video Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.01696","kind":"arxiv","version":1},"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:e4cdf2f43931b9c7c432872963702029eafdd223b249ec56b94cebdd5254f309","target":"record","created_at":"2026-07-05T03:11:33Z","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":"8ef2ace877d2da0564b481ea11993d1500484fd655548c672f59090aff591fe3","cross_cats_sorted":["cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-09-03T18:27:52Z","title_canon_sha256":"e5e86a85b012a6c90c569fc3a21ff32be80b46e869135b89fbb4796bac9a108f"},"schema_version":"1.0","source":{"id":"2109.01696","kind":"arxiv","version":1}},"canonical_sha256":"c3c1a5ca66212daafd050eecebc371fb0a5a08982df702d319bc2a5ab8737d63","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c3c1a5ca66212daafd050eecebc371fb0a5a08982df702d319bc2a5ab8737d63","first_computed_at":"2026-07-05T03:11:33.825540Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:11:33.825540Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2ZQBsBNScvChNetFA/1YDrIwGDErejwFCOIK1CCLwMNrjQXBfOSxuiuN8I61ashzi8Krhx4r6hJN7hdZZG+fCg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:11:33.826153Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.01696","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4cdf2f43931b9c7c432872963702029eafdd223b249ec56b94cebdd5254f309","sha256:bee6e3ff3bbfdc080f2c4b9d61b16753b341e3ce801255c391f8190e333a9cf1"],"state_sha256":"fd1e2fcb5d9e31852e8f196dc1e0d0c10a4ad6384028c38d1118a121c0306cbd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mvr0PUQeWdt9TwBT8Gbw1ococho1JdrcFojlv1RG5yfYbm1f01U6Hw/LRTeC8F+wGC7o0ldEOTYqROLCdSKkCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T04:32:24.289732Z","bundle_sha256":"27501cf2a515874f7609f537d6a427c7594475dc500d41c6d40bae2a89042ba1"}}