{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:KUD6WF54FQTC4KQFVKNT5ICHUO","short_pith_number":"pith:KUD6WF54","canonical_record":{"source":{"id":"2404.05666","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-08T16:51:19Z","cross_cats_sorted":[],"title_canon_sha256":"9ccfd98a261ffd04b2071cda1fa0ca01a96e68567c1f4e8906289a851e22e167","abstract_canon_sha256":"792ac73bc251f5978b01658e8d450273251ece17d62ddee586b4c93b16f7154f"},"schema_version":"1.0"},"canonical_sha256":"5507eb17bc2c262e2a05aa9b3ea047a3a1b071bbfdda8613bb85a2417ee34384","source":{"kind":"arxiv","id":"2404.05666","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.05666","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"arxiv_version","alias_value":"2404.05666v1","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.05666","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"pith_short_12","alias_value":"KUD6WF54FQTC","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"pith_short_16","alias_value":"KUD6WF54FQTC4KQF","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"pith_short_8","alias_value":"KUD6WF54","created_at":"2026-07-05T08:05:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:KUD6WF54FQTC4KQFVKNT5ICHUO","target":"record","payload":{"canonical_record":{"source":{"id":"2404.05666","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-08T16:51:19Z","cross_cats_sorted":[],"title_canon_sha256":"9ccfd98a261ffd04b2071cda1fa0ca01a96e68567c1f4e8906289a851e22e167","abstract_canon_sha256":"792ac73bc251f5978b01658e8d450273251ece17d62ddee586b4c93b16f7154f"},"schema_version":"1.0"},"canonical_sha256":"5507eb17bc2c262e2a05aa9b3ea047a3a1b071bbfdda8613bb85a2417ee34384","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:05:43.994531Z","signature_b64":"MtMzFPNmGWoReg3/qQRSsWb+O46wF3MC2VDuENWzGkH+blrzl4VNbxL3xy/Fe+Q03VJ9MaL+c3yLRXlHJOvsAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5507eb17bc2c262e2a05aa9b3ea047a3a1b071bbfdda8613bb85a2417ee34384","last_reissued_at":"2026-07-05T08:05:43.994023Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:05:43.994023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.05666","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":"2026-07-05T08:05:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DudMNXLqamLjlJn/rc8+e81QZBCj0KeDETOSm93J6ZUoldghODQCo3oHHnLmvAK+Z8JXm9H9zMeltDRmz86YDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T18:30:04.699628Z"},"content_sha256":"013407b8ee14e4a783c4b1d8c8a323bf13ebfb3a0a0da9a89b7d31d17eb34f84","schema_version":"1.0","event_id":"sha256:013407b8ee14e4a783c4b1d8c8a323bf13ebfb3a0a0da9a89b7d31d17eb34f84"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:KUD6WF54FQTC4KQFVKNT5ICHUO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"YaART: Yet Another ART Rendering Technology","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alexander Markovich, Alexander Shishenya, Alexander Tselousov, Alexander Ustyuzhanin, Alexey Kirillov, Anastasiia Tabisheva, Artem Babenko, Artemii Shvetsov, Artem Khurshudov, Artem Konev, Daniil Shlenskii, Denis Kuznedelev, Dmitrii Kornilov, Eugene Lyapustin, Grigoriy Livshits, Liubov Chubarova, Marina Kaminskaia, Mikhail Romanov, Nikita Vinokurov, Sergei Ovcharenko, Sergey Kastryulin, Valentin Khrulkov, Valerii Startsev","submitted_at":"2024-04-08T16:51:19Z","abstract_excerpt":"In the rapidly progressing field of generative models, the development of efficient and high-fidelity text-to-image diffusion systems represents a significant frontier. This study introduces YaART, a novel production-grade text-to-image cascaded diffusion model aligned to human preferences using Reinforcement Learning from Human Feedback (RLHF). During the development of YaART, we especially focus on the choices of the model and training dataset sizes, the aspects that were not systematically investigated for text-to-image cascaded diffusion models before. In particular, we comprehensively ana"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.05666","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/2404.05666/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":"2026-07-05T08:05:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RwV3W+4WHamcQ2bYJ/9q0kQYd3pLC8KvAlW8ZhbP39TiiQfHJsKwQe0Tq0OOPwCS8/u+0bDTJrheSpJS/6LfCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-12T18:30:04.700015Z"},"content_sha256":"07f775fc9a996f91e81a9901ba858fc725e566bf73db639be12ab683cab7b9b0","schema_version":"1.0","event_id":"sha256:07f775fc9a996f91e81a9901ba858fc725e566bf73db639be12ab683cab7b9b0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KUD6WF54FQTC4KQFVKNT5ICHUO/bundle.json","state_url":"https://pith.science/pith/KUD6WF54FQTC4KQFVKNT5ICHUO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KUD6WF54FQTC4KQFVKNT5ICHUO/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":"2026-07-12T18:30:04Z","links":{"resolver":"https://pith.science/pith/KUD6WF54FQTC4KQFVKNT5ICHUO","bundle":"https://pith.science/pith/KUD6WF54FQTC4KQFVKNT5ICHUO/bundle.json","state":"https://pith.science/pith/KUD6WF54FQTC4KQFVKNT5ICHUO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KUD6WF54FQTC4KQFVKNT5ICHUO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KUD6WF54FQTC4KQFVKNT5ICHUO","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":"792ac73bc251f5978b01658e8d450273251ece17d62ddee586b4c93b16f7154f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-08T16:51:19Z","title_canon_sha256":"9ccfd98a261ffd04b2071cda1fa0ca01a96e68567c1f4e8906289a851e22e167"},"schema_version":"1.0","source":{"id":"2404.05666","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.05666","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"arxiv_version","alias_value":"2404.05666v1","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.05666","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"pith_short_12","alias_value":"KUD6WF54FQTC","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"pith_short_16","alias_value":"KUD6WF54FQTC4KQF","created_at":"2026-07-05T08:05:43Z"},{"alias_kind":"pith_short_8","alias_value":"KUD6WF54","created_at":"2026-07-05T08:05:43Z"}],"graph_snapshots":[{"event_id":"sha256:07f775fc9a996f91e81a9901ba858fc725e566bf73db639be12ab683cab7b9b0","target":"graph","created_at":"2026-07-05T08:05:43Z","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/2404.05666/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In the rapidly progressing field of generative models, the development of efficient and high-fidelity text-to-image diffusion systems represents a significant frontier. This study introduces YaART, a novel production-grade text-to-image cascaded diffusion model aligned to human preferences using Reinforcement Learning from Human Feedback (RLHF). During the development of YaART, we especially focus on the choices of the model and training dataset sizes, the aspects that were not systematically investigated for text-to-image cascaded diffusion models before. In particular, we comprehensively ana","authors_text":"Alexander Markovich, Alexander Shishenya, Alexander Tselousov, Alexander Ustyuzhanin, Alexey Kirillov, Anastasiia Tabisheva, Artem Babenko, Artemii Shvetsov, Artem Khurshudov, Artem Konev, Daniil Shlenskii, Denis Kuznedelev, Dmitrii Kornilov, Eugene Lyapustin, Grigoriy Livshits, Liubov Chubarova, Marina Kaminskaia, Mikhail Romanov, Nikita Vinokurov, Sergei Ovcharenko, Sergey Kastryulin, Valentin Khrulkov, Valerii Startsev","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-08T16:51:19Z","title":"YaART: Yet Another ART Rendering Technology"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.05666","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":"sha256:013407b8ee14e4a783c4b1d8c8a323bf13ebfb3a0a0da9a89b7d31d17eb34f84","target":"record","created_at":"2026-07-05T08:05:43Z","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":"792ac73bc251f5978b01658e8d450273251ece17d62ddee586b4c93b16f7154f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-08T16:51:19Z","title_canon_sha256":"9ccfd98a261ffd04b2071cda1fa0ca01a96e68567c1f4e8906289a851e22e167"},"schema_version":"1.0","source":{"id":"2404.05666","kind":"arxiv","version":1}},"canonical_sha256":"5507eb17bc2c262e2a05aa9b3ea047a3a1b071bbfdda8613bb85a2417ee34384","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5507eb17bc2c262e2a05aa9b3ea047a3a1b071bbfdda8613bb85a2417ee34384","first_computed_at":"2026-07-05T08:05:43.994023Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:05:43.994023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MtMzFPNmGWoReg3/qQRSsWb+O46wF3MC2VDuENWzGkH+blrzl4VNbxL3xy/Fe+Q03VJ9MaL+c3yLRXlHJOvsAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:05:43.994531Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.05666","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:013407b8ee14e4a783c4b1d8c8a323bf13ebfb3a0a0da9a89b7d31d17eb34f84","sha256:07f775fc9a996f91e81a9901ba858fc725e566bf73db639be12ab683cab7b9b0"],"state_sha256":"dcf43df907d591b1b65c60d0ec242d34152788b752861268251bce7c908aa9a7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ilrqUqY+768QOe+3Votp0Ks3zAR8E/4rPcSxCMne/TcOok0KRyE9hqU8olygT2pGMHSQIQ9HDM0NdrgBLVAABw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-12T18:30:04.702656Z","bundle_sha256":"832785a7d8f1308753a202ae0787141117de57970d37fc7a853c5605789756d2"}}