{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ZCDESSCQRO6PJQL5ODM5YORSDG","short_pith_number":"pith:ZCDESSCQ","canonical_record":{"source":{"id":"2412.15156","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-19T18:32:21Z","cross_cats_sorted":["cs.CL","cs.MM"],"title_canon_sha256":"a582188e40c3188fa412b5b6ee0a42a21316f601c58faabad2fac6a6437224bd","abstract_canon_sha256":"cce96b3a8c7220f80725a54b04e54cb958d95c45e6515702fb9475608aed5f16"},"schema_version":"1.0"},"canonical_sha256":"c8864948508bbcf4c17d70d9dc3a3219bb30015da97cefefa732b2cc016aa524","source":{"kind":"arxiv","id":"2412.15156","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.15156","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"arxiv_version","alias_value":"2412.15156v1","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.15156","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"pith_short_12","alias_value":"ZCDESSCQRO6P","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"pith_short_16","alias_value":"ZCDESSCQRO6PJQL5","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"pith_short_8","alias_value":"ZCDESSCQ","created_at":"2026-07-05T09:51:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ZCDESSCQRO6PJQL5ODM5YORSDG","target":"record","payload":{"canonical_record":{"source":{"id":"2412.15156","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-19T18:32:21Z","cross_cats_sorted":["cs.CL","cs.MM"],"title_canon_sha256":"a582188e40c3188fa412b5b6ee0a42a21316f601c58faabad2fac6a6437224bd","abstract_canon_sha256":"cce96b3a8c7220f80725a54b04e54cb958d95c45e6515702fb9475608aed5f16"},"schema_version":"1.0"},"canonical_sha256":"c8864948508bbcf4c17d70d9dc3a3219bb30015da97cefefa732b2cc016aa524","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:51:58.697747Z","signature_b64":"qhPJHrAJ+I0+hZ5pQ35PDEyg0Dmd4Q9+LKbEA1WelupJNWP07lLV6+q/E+2w++1vY0CyTgYU64SwMKHOGE2MCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c8864948508bbcf4c17d70d9dc3a3219bb30015da97cefefa732b2cc016aa524","last_reissued_at":"2026-07-05T09:51:58.694965Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:51:58.694965Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.15156","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":"2026-07-05T09:51:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HzltVkynDIqAVuJv1CP62dpjyyTDfHWlQb7vkeh26cE9JkXZ88OM8gqgtFf6NSfGJfdseH1ol7vnajrqPmcbBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T20:40:30.625149Z"},"content_sha256":"5b1d44d0961e85c183a9f9172ad1b34ab4441ae126bb6a2c4a8b717249b0806f","schema_version":"1.0","event_id":"sha256:5b1d44d0961e85c183a9f9172ad1b34ab4441ae126bb6a2c4a8b717249b0806f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ZCDESSCQRO6PJQL5ODM5YORSDG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned LLM","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.MM"],"primary_cat":"cs.CV","authors_text":"Chongjian Ge, Jiacheng Zhang, Jie Wu, Peize Sun, Ping Luo, Shilong Zhang, Shoufa Chen, Weifeng Chen, Weilin Huang, Wenqi Shao, Xuefeng Xiao, Yatai Ji","submitted_at":"2024-12-19T18:32:21Z","abstract_excerpt":"Text-to-video models have made remarkable advancements through optimization on high-quality text-video pairs, where the textual prompts play a pivotal role in determining quality of output videos. However, achieving the desired output often entails multiple revisions and iterative inference to refine user-provided prompts. Current automatic methods for refining prompts encounter challenges such as Modality-Inconsistency, Cost-Discrepancy, and Model-Unaware when applied to text-to-video diffusion models. To address these problem, we introduce an LLM-based prompt adaptation framework, termed as "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.15156","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/2412.15156/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":"2026-07-05T09:51:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+WTJr2F2+GIaKqI9ZWQHKoCxLebhtZvt/mEsbEyl58ormp/JuKDK5jCeBgTy6I/XWqA32tyGTfgL9h8+pXz1Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T20:40:30.625559Z"},"content_sha256":"a32a342fd8e4d7786c7eb45beec60b57bb25a099c2052fcf4304fc238aa9c8ee","schema_version":"1.0","event_id":"sha256:a32a342fd8e4d7786c7eb45beec60b57bb25a099c2052fcf4304fc238aa9c8ee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZCDESSCQRO6PJQL5ODM5YORSDG/bundle.json","state_url":"https://pith.science/pith/ZCDESSCQRO6PJQL5ODM5YORSDG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZCDESSCQRO6PJQL5ODM5YORSDG/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":"2026-07-06T20:40:30Z","links":{"resolver":"https://pith.science/pith/ZCDESSCQRO6PJQL5ODM5YORSDG","bundle":"https://pith.science/pith/ZCDESSCQRO6PJQL5ODM5YORSDG/bundle.json","state":"https://pith.science/pith/ZCDESSCQRO6PJQL5ODM5YORSDG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZCDESSCQRO6PJQL5ODM5YORSDG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ZCDESSCQRO6PJQL5ODM5YORSDG","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":"cce96b3a8c7220f80725a54b04e54cb958d95c45e6515702fb9475608aed5f16","cross_cats_sorted":["cs.CL","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-19T18:32:21Z","title_canon_sha256":"a582188e40c3188fa412b5b6ee0a42a21316f601c58faabad2fac6a6437224bd"},"schema_version":"1.0","source":{"id":"2412.15156","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.15156","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"arxiv_version","alias_value":"2412.15156v1","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.15156","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"pith_short_12","alias_value":"ZCDESSCQRO6P","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"pith_short_16","alias_value":"ZCDESSCQRO6PJQL5","created_at":"2026-07-05T09:51:58Z"},{"alias_kind":"pith_short_8","alias_value":"ZCDESSCQ","created_at":"2026-07-05T09:51:58Z"}],"graph_snapshots":[{"event_id":"sha256:a32a342fd8e4d7786c7eb45beec60b57bb25a099c2052fcf4304fc238aa9c8ee","target":"graph","created_at":"2026-07-05T09:51:58Z","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/2412.15156/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text-to-video models have made remarkable advancements through optimization on high-quality text-video pairs, where the textual prompts play a pivotal role in determining quality of output videos. However, achieving the desired output often entails multiple revisions and iterative inference to refine user-provided prompts. Current automatic methods for refining prompts encounter challenges such as Modality-Inconsistency, Cost-Discrepancy, and Model-Unaware when applied to text-to-video diffusion models. To address these problem, we introduce an LLM-based prompt adaptation framework, termed as ","authors_text":"Chongjian Ge, Jiacheng Zhang, Jie Wu, Peize Sun, Ping Luo, Shilong Zhang, Shoufa Chen, Weifeng Chen, Weilin Huang, Wenqi Shao, Xuefeng Xiao, Yatai Ji","cross_cats":["cs.CL","cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-19T18:32:21Z","title":"Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned LLM"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.15156","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":"sha256:5b1d44d0961e85c183a9f9172ad1b34ab4441ae126bb6a2c4a8b717249b0806f","target":"record","created_at":"2026-07-05T09:51:58Z","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":"cce96b3a8c7220f80725a54b04e54cb958d95c45e6515702fb9475608aed5f16","cross_cats_sorted":["cs.CL","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-19T18:32:21Z","title_canon_sha256":"a582188e40c3188fa412b5b6ee0a42a21316f601c58faabad2fac6a6437224bd"},"schema_version":"1.0","source":{"id":"2412.15156","kind":"arxiv","version":1}},"canonical_sha256":"c8864948508bbcf4c17d70d9dc3a3219bb30015da97cefefa732b2cc016aa524","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c8864948508bbcf4c17d70d9dc3a3219bb30015da97cefefa732b2cc016aa524","first_computed_at":"2026-07-05T09:51:58.694965Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:51:58.694965Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qhPJHrAJ+I0+hZ5pQ35PDEyg0Dmd4Q9+LKbEA1WelupJNWP07lLV6+q/E+2w++1vY0CyTgYU64SwMKHOGE2MCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:51:58.697747Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.15156","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5b1d44d0961e85c183a9f9172ad1b34ab4441ae126bb6a2c4a8b717249b0806f","sha256:a32a342fd8e4d7786c7eb45beec60b57bb25a099c2052fcf4304fc238aa9c8ee"],"state_sha256":"8de64d861e43ca6abd73a87c7bdbe307bb9a5ea64d6e4c5f126ebfc9fafdb82c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vrYoo1c4k9xw7iY7QyGJRNvig96aPJgKse6cqyQPtaJVz+9pQ3AJyBuUEp3DnK0HfJ3qIM2HHJ/1hOgKDlivAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T20:40:30.627601Z","bundle_sha256":"edb7879e80af459d7e9dda4239bd156c2d5e8a45e2519c390326367f9a6be3a6"}}