{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:IHS7JT5X2VSN4QLL2RHZDBZMCE","short_pith_number":"pith:IHS7JT5X","canonical_record":{"source":{"id":"2411.04942","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-07T18:20:28Z","cross_cats_sorted":[],"title_canon_sha256":"ccd4b4de11b42aa270be73b8b63c3d1b0ea1eb3f813c7286fda2ae6a9e3ee297","abstract_canon_sha256":"4b78fe6781de3370e975c4d76f2930c9b905ed00c875cf3c56a13c8812b42698"},"schema_version":"1.0"},"canonical_sha256":"41e5f4cfb7d564de416bd44f91872c110332db40a7f1e241dcd5dc82cd6276b7","source":{"kind":"arxiv","id":"2411.04942","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.04942","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"arxiv_version","alias_value":"2411.04942v1","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.04942","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"pith_short_12","alias_value":"IHS7JT5X2VSN","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"pith_short_16","alias_value":"IHS7JT5X2VSN4QLL","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"pith_short_8","alias_value":"IHS7JT5X","created_at":"2026-07-05T09:32:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:IHS7JT5X2VSN4QLL2RHZDBZMCE","target":"record","payload":{"canonical_record":{"source":{"id":"2411.04942","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-07T18:20:28Z","cross_cats_sorted":[],"title_canon_sha256":"ccd4b4de11b42aa270be73b8b63c3d1b0ea1eb3f813c7286fda2ae6a9e3ee297","abstract_canon_sha256":"4b78fe6781de3370e975c4d76f2930c9b905ed00c875cf3c56a13c8812b42698"},"schema_version":"1.0"},"canonical_sha256":"41e5f4cfb7d564de416bd44f91872c110332db40a7f1e241dcd5dc82cd6276b7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:32:36.500575Z","signature_b64":"2e9sF0eShhYUoDoHiY8q1+WPbgkr2CQShnnGi1vWU+tFKXBBHRhnOyf26ojp6yB5EnAYFQ0R8emXJ/Ins6VsBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"41e5f4cfb7d564de416bd44f91872c110332db40a7f1e241dcd5dc82cd6276b7","last_reissued_at":"2026-07-05T09:32:36.500082Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:32:36.500082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.04942","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":"2026-07-05T09:32:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LIiq55O3LwXAeMSHUCfHMyT8/f6yZYmw2irXZwfEi8Gncp38+3DM2h1kFUCbulCR3PYk8h1giNC5roSP1cyTBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T06:30:45.617985Z"},"content_sha256":"140e63a856af3e045a9807736d64e00147aa5d21119e28360b8793c534996a80","schema_version":"1.0","event_id":"sha256:140e63a856af3e045a9807736d64e00147aa5d21119e28360b8793c534996a80"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:IHS7JT5X2VSN4QLL2RHZDBZMCE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Reinforcement Learning-Based Automatic Video Editing Method Using Pre-trained Vision-Language Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Feifei Li, Nan Xiao, Panwen Hu, Rui Huang, Yongquan Chen","submitted_at":"2024-11-07T18:20:28Z","abstract_excerpt":"In this era of videos, automatic video editing techniques attract more and more attention from industry and academia since they can reduce workloads and lower the requirements for human editors. Existing automatic editing systems are mainly scene- or event-specific, e.g., soccer game broadcasting, yet the automatic systems for general editing, e.g., movie or vlog editing which covers various scenes and events, were rarely studied before, and converting the event-driven editing method to a general scene is nontrivial. In this paper, we propose a two-stage scheme for general editing. Firstly, un"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.04942","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/2411.04942/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":"2026-07-05T09:32:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3OMTWtevsCco0Dr5NFPeWKWYqLoDVrpwoHX6PqFODTENm0ceoxOPLZJrdOdvxSuK5ln4O5cpe9DXDSEEDQssCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T06:30:45.618667Z"},"content_sha256":"b2a95b59c208277753652ca6d6a5beb50be854f7f21b3a6195a65da584dd0baf","schema_version":"1.0","event_id":"sha256:b2a95b59c208277753652ca6d6a5beb50be854f7f21b3a6195a65da584dd0baf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IHS7JT5X2VSN4QLL2RHZDBZMCE/bundle.json","state_url":"https://pith.science/pith/IHS7JT5X2VSN4QLL2RHZDBZMCE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IHS7JT5X2VSN4QLL2RHZDBZMCE/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":"2026-08-05T06:30:45Z","links":{"resolver":"https://pith.science/pith/IHS7JT5X2VSN4QLL2RHZDBZMCE","bundle":"https://pith.science/pith/IHS7JT5X2VSN4QLL2RHZDBZMCE/bundle.json","state":"https://pith.science/pith/IHS7JT5X2VSN4QLL2RHZDBZMCE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IHS7JT5X2VSN4QLL2RHZDBZMCE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:IHS7JT5X2VSN4QLL2RHZDBZMCE","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":"4b78fe6781de3370e975c4d76f2930c9b905ed00c875cf3c56a13c8812b42698","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-07T18:20:28Z","title_canon_sha256":"ccd4b4de11b42aa270be73b8b63c3d1b0ea1eb3f813c7286fda2ae6a9e3ee297"},"schema_version":"1.0","source":{"id":"2411.04942","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.04942","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"arxiv_version","alias_value":"2411.04942v1","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.04942","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"pith_short_12","alias_value":"IHS7JT5X2VSN","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"pith_short_16","alias_value":"IHS7JT5X2VSN4QLL","created_at":"2026-07-05T09:32:36Z"},{"alias_kind":"pith_short_8","alias_value":"IHS7JT5X","created_at":"2026-07-05T09:32:36Z"}],"graph_snapshots":[{"event_id":"sha256:b2a95b59c208277753652ca6d6a5beb50be854f7f21b3a6195a65da584dd0baf","target":"graph","created_at":"2026-07-05T09:32:36Z","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/2411.04942/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this era of videos, automatic video editing techniques attract more and more attention from industry and academia since they can reduce workloads and lower the requirements for human editors. Existing automatic editing systems are mainly scene- or event-specific, e.g., soccer game broadcasting, yet the automatic systems for general editing, e.g., movie or vlog editing which covers various scenes and events, were rarely studied before, and converting the event-driven editing method to a general scene is nontrivial. In this paper, we propose a two-stage scheme for general editing. Firstly, un","authors_text":"Feifei Li, Nan Xiao, Panwen Hu, Rui Huang, Yongquan Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-07T18:20:28Z","title":"A Reinforcement Learning-Based Automatic Video Editing Method Using Pre-trained Vision-Language Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.04942","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":"sha256:140e63a856af3e045a9807736d64e00147aa5d21119e28360b8793c534996a80","target":"record","created_at":"2026-07-05T09:32:36Z","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":"4b78fe6781de3370e975c4d76f2930c9b905ed00c875cf3c56a13c8812b42698","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-07T18:20:28Z","title_canon_sha256":"ccd4b4de11b42aa270be73b8b63c3d1b0ea1eb3f813c7286fda2ae6a9e3ee297"},"schema_version":"1.0","source":{"id":"2411.04942","kind":"arxiv","version":1}},"canonical_sha256":"41e5f4cfb7d564de416bd44f91872c110332db40a7f1e241dcd5dc82cd6276b7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"41e5f4cfb7d564de416bd44f91872c110332db40a7f1e241dcd5dc82cd6276b7","first_computed_at":"2026-07-05T09:32:36.500082Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:32:36.500082Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2e9sF0eShhYUoDoHiY8q1+WPbgkr2CQShnnGi1vWU+tFKXBBHRhnOyf26ojp6yB5EnAYFQ0R8emXJ/Ins6VsBg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:32:36.500575Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.04942","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:140e63a856af3e045a9807736d64e00147aa5d21119e28360b8793c534996a80","sha256:b2a95b59c208277753652ca6d6a5beb50be854f7f21b3a6195a65da584dd0baf"],"state_sha256":"5addfb8e8b327615e131c834e6dee5fd965ada9a2c6c532a82bebc40082bd176"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ELaE9oCbUcLs+1oegP5EQDovgkIM9z6GQBNs9RCGiFzXacXw/gWPBnwHzp3X1roPBgP/cE/kV/3DHL0CfCh8DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T06:30:45.623324Z","bundle_sha256":"94728461a53799d0bee01ae787717fedc0a37ab9a864b461daf652a9f60692d0"}}