{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:MXZ7FSE2CA4366ZTDGOLJ75KWQ","short_pith_number":"pith:MXZ7FSE2","canonical_record":{"source":{"id":"2409.11340","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-17T16:42:46Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6982f19dd10464e11f762f4f7f083cf48f7eaefb0373666d2faf4a31a4df6a77","abstract_canon_sha256":"fc79f1cf745931adff0ace356e728bcca4e71c904f23ee50fcb579cbfc7ea286"},"schema_version":"1.0"},"canonical_sha256":"65f3f2c89a1039bf7b33199cb4ffaab41dc96402d61385ee8c8ed97dfd7129bb","source":{"kind":"arxiv","id":"2409.11340","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.11340","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"arxiv_version","alias_value":"2409.11340v2","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.11340","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"pith_short_12","alias_value":"MXZ7FSE2CA43","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"pith_short_16","alias_value":"MXZ7FSE2CA4366ZT","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"pith_short_8","alias_value":"MXZ7FSE2","created_at":"2026-07-05T09:38:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:MXZ7FSE2CA4366ZTDGOLJ75KWQ","target":"record","payload":{"canonical_record":{"source":{"id":"2409.11340","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-17T16:42:46Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6982f19dd10464e11f762f4f7f083cf48f7eaefb0373666d2faf4a31a4df6a77","abstract_canon_sha256":"fc79f1cf745931adff0ace356e728bcca4e71c904f23ee50fcb579cbfc7ea286"},"schema_version":"1.0"},"canonical_sha256":"65f3f2c89a1039bf7b33199cb4ffaab41dc96402d61385ee8c8ed97dfd7129bb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:38:29.589199Z","signature_b64":"jYqRRY+PoRM0OLmC42rRGk+Fxj0ckSpN9pmNCwqevHalfPt+IYp19HsRR+jWqSf9qc2D4pwrJhdmGss7nTUvDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"65f3f2c89a1039bf7b33199cb4ffaab41dc96402d61385ee8c8ed97dfd7129bb","last_reissued_at":"2026-07-05T09:38:29.588755Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:38:29.588755Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.11340","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":"2026-07-05T09:38:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0fGwFSJY8Hrwy3po5rpL6TY4g+kh68mZPL6qN8zUeFGKNRbS0xlCpPkw3RGt4Fvv3VEYG2J+bmqceAGoRPCNBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:04:05.807436Z"},"content_sha256":"98356993e023d04bb6eb60dcdc6b91fc22da8f2d796a73733875e381ec80f72d","schema_version":"1.0","event_id":"sha256:98356993e023d04bb6eb60dcdc6b91fc22da8f2d796a73733875e381ec80f72d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:MXZ7FSE2CA4366ZTDGOLJ75KWQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"OmniGen: Unified Image Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Chaofan Li, Huaying Yuan, Junjie Zhou, Ruiran Yan, Shitao Xiao, Shuting Wang, Tiejun Huang, Xingrun Xing, Yueze Wang, Zheng Liu","submitted_at":"2024-09-17T16:42:46Z","abstract_excerpt":"The emergence of Large Language Models (LLMs) has unified language generation tasks and revolutionized human-machine interaction. However, in the realm of image generation, a unified model capable of handling various tasks within a single framework remains largely unexplored. In this work, we introduce OmniGen, a new diffusion model for unified image generation. OmniGen is characterized by the following features: 1) Unification: OmniGen not only demonstrates text-to-image generation capabilities but also inherently supports various downstream tasks, such as image editing, subject-driven genera"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.11340","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/2409.11340/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":"2026-07-05T09:38:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d3V5vHjR+ItL0hKXZbAVcy4HOB1tfFS1UXFcd+Gr3htu7AIqcXTY5hgs9aZqT41XxgzkVkFDIUcrO9pHTVtTDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:04:05.807734Z"},"content_sha256":"7bd3f1442184f63f792e5dc4866d9bb9b89e68f013e3cf76da163e067de554ba","schema_version":"1.0","event_id":"sha256:7bd3f1442184f63f792e5dc4866d9bb9b89e68f013e3cf76da163e067de554ba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MXZ7FSE2CA4366ZTDGOLJ75KWQ/bundle.json","state_url":"https://pith.science/pith/MXZ7FSE2CA4366ZTDGOLJ75KWQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MXZ7FSE2CA4366ZTDGOLJ75KWQ/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":"2026-08-05T18:04:05Z","links":{"resolver":"https://pith.science/pith/MXZ7FSE2CA4366ZTDGOLJ75KWQ","bundle":"https://pith.science/pith/MXZ7FSE2CA4366ZTDGOLJ75KWQ/bundle.json","state":"https://pith.science/pith/MXZ7FSE2CA4366ZTDGOLJ75KWQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MXZ7FSE2CA4366ZTDGOLJ75KWQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MXZ7FSE2CA4366ZTDGOLJ75KWQ","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":"fc79f1cf745931adff0ace356e728bcca4e71c904f23ee50fcb579cbfc7ea286","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-17T16:42:46Z","title_canon_sha256":"6982f19dd10464e11f762f4f7f083cf48f7eaefb0373666d2faf4a31a4df6a77"},"schema_version":"1.0","source":{"id":"2409.11340","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.11340","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"arxiv_version","alias_value":"2409.11340v2","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.11340","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"pith_short_12","alias_value":"MXZ7FSE2CA43","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"pith_short_16","alias_value":"MXZ7FSE2CA4366ZT","created_at":"2026-07-05T09:38:29Z"},{"alias_kind":"pith_short_8","alias_value":"MXZ7FSE2","created_at":"2026-07-05T09:38:29Z"}],"graph_snapshots":[{"event_id":"sha256:7bd3f1442184f63f792e5dc4866d9bb9b89e68f013e3cf76da163e067de554ba","target":"graph","created_at":"2026-07-05T09:38:29Z","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/2409.11340/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The emergence of Large Language Models (LLMs) has unified language generation tasks and revolutionized human-machine interaction. However, in the realm of image generation, a unified model capable of handling various tasks within a single framework remains largely unexplored. In this work, we introduce OmniGen, a new diffusion model for unified image generation. OmniGen is characterized by the following features: 1) Unification: OmniGen not only demonstrates text-to-image generation capabilities but also inherently supports various downstream tasks, such as image editing, subject-driven genera","authors_text":"Chaofan Li, Huaying Yuan, Junjie Zhou, Ruiran Yan, Shitao Xiao, Shuting Wang, Tiejun Huang, Xingrun Xing, Yueze Wang, Zheng Liu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-17T16:42:46Z","title":"OmniGen: Unified Image Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.11340","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":"sha256:98356993e023d04bb6eb60dcdc6b91fc22da8f2d796a73733875e381ec80f72d","target":"record","created_at":"2026-07-05T09:38:29Z","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":"fc79f1cf745931adff0ace356e728bcca4e71c904f23ee50fcb579cbfc7ea286","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-17T16:42:46Z","title_canon_sha256":"6982f19dd10464e11f762f4f7f083cf48f7eaefb0373666d2faf4a31a4df6a77"},"schema_version":"1.0","source":{"id":"2409.11340","kind":"arxiv","version":2}},"canonical_sha256":"65f3f2c89a1039bf7b33199cb4ffaab41dc96402d61385ee8c8ed97dfd7129bb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"65f3f2c89a1039bf7b33199cb4ffaab41dc96402d61385ee8c8ed97dfd7129bb","first_computed_at":"2026-07-05T09:38:29.588755Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:38:29.588755Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jYqRRY+PoRM0OLmC42rRGk+Fxj0ckSpN9pmNCwqevHalfPt+IYp19HsRR+jWqSf9qc2D4pwrJhdmGss7nTUvDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:38:29.589199Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.11340","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:98356993e023d04bb6eb60dcdc6b91fc22da8f2d796a73733875e381ec80f72d","sha256:7bd3f1442184f63f792e5dc4866d9bb9b89e68f013e3cf76da163e067de554ba"],"state_sha256":"ced8d784906ec4cf843d596f133a7d1533470c5252adb76d985625fd80392b93"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k1z68dWQFRdGsyDAQBz4pIT5xTHVxbIvfA8TKR7yqQ/YMYVR+P7wavcs2gZHEiXMdRXBBIp5mczdNH7sn/AuDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T18:04:05.811085Z","bundle_sha256":"aa9da9deb6a4f196ff896f05b92bddbdb3f8244225b366b77d017ab1b38bc06b"}}