{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:WZO5S3VFWLSAQJLCO7NCNEEEGM","short_pith_number":"pith:WZO5S3VF","canonical_record":{"source":{"id":"2411.17522","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-26T15:30:48Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"b5b697cc2d67749751e3277d7a306aa1cad0f3b37cce0ab7c0c40bbca96f1a1c","abstract_canon_sha256":"b1bfe6217ece81fb0033d0c0328c6aa8050c96122393866a8392822fb0e3809d"},"schema_version":"1.0"},"canonical_sha256":"b65dd96ea5b2e408256277da2690843307072c077919be99b160b68651f0d9f3","source":{"kind":"arxiv","id":"2411.17522","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.17522","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"arxiv_version","alias_value":"2411.17522v1","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.17522","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"pith_short_12","alias_value":"WZO5S3VFWLSA","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"pith_short_16","alias_value":"WZO5S3VFWLSAQJLC","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"pith_short_8","alias_value":"WZO5S3VF","created_at":"2026-07-05T09:40:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:WZO5S3VFWLSAQJLCO7NCNEEEGM","target":"record","payload":{"canonical_record":{"source":{"id":"2411.17522","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-26T15:30:48Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"b5b697cc2d67749751e3277d7a306aa1cad0f3b37cce0ab7c0c40bbca96f1a1c","abstract_canon_sha256":"b1bfe6217ece81fb0033d0c0328c6aa8050c96122393866a8392822fb0e3809d"},"schema_version":"1.0"},"canonical_sha256":"b65dd96ea5b2e408256277da2690843307072c077919be99b160b68651f0d9f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:40:48.318802Z","signature_b64":"7lGmP5uSbKeG4Ai69NKboiZEpHW28tIhRS8xfTNVAjpJHeYoAnWqlEwi3kidaUjPILcmGx1CtE+iy1qs23oXDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b65dd96ea5b2e408256277da2690843307072c077919be99b160b68651f0d9f3","last_reissued_at":"2026-07-05T09:40:48.318299Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:40:48.318299Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.17522","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":"2026-07-05T09:40:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8ZF/pxzPuSZv29pPw+10Lkl75knxmAFpb7txwK6/NgU4UpGHT9v/HCXEjSvtxuBfK3yof37FUDEw/ijJGPzTDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T14:14:25.483949Z"},"content_sha256":"1915dfd2e4ac1ee39374d9f074ffb868c516e20cde4a39e208aaf03a91cf93b1","schema_version":"1.0","event_id":"sha256:1915dfd2e4ac1ee39374d9f074ffb868c516e20cde4a39e208aaf03a91cf93b1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:WZO5S3VFWLSAQJLCO7NCNEEEGM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.LG"],"primary_cat":"stat.ML","authors_text":"Han Liu, Jerry Yao-Chieh Hu, Minshuo Chen, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang","submitted_at":"2024-11-26T15:30:48Z","abstract_excerpt":"We investigate the approximation and estimation rates of conditional diffusion transformers (DiTs) with classifier-free guidance. We present a comprehensive analysis for ``in-context'' conditional DiTs under four common data assumptions. We show that both conditional DiTs and their latent variants lead to the minimax optimality of unconditional DiTs under identified settings. Specifically, we discretize the input domains into infinitesimal grids and then perform a term-by-term Taylor expansion on the conditional diffusion score function under H\\\"older smooth data assumption. This enables fine-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.17522","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/2411.17522/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":"2026-07-05T09:40:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x2akH14P/b1xp46sFLkeT+5zZDbN5mk9fFPA5tLuIwjsQ3FPyZ3zKI/8khLcVj9afVXiSemf/ZDyz++clZFBDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T14:14:25.484493Z"},"content_sha256":"d70ef8332ddafb63ee0999310757c33fbd1e74e6ef0c256eab102cebf28108e3","schema_version":"1.0","event_id":"sha256:d70ef8332ddafb63ee0999310757c33fbd1e74e6ef0c256eab102cebf28108e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WZO5S3VFWLSAQJLCO7NCNEEEGM/bundle.json","state_url":"https://pith.science/pith/WZO5S3VFWLSAQJLCO7NCNEEEGM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WZO5S3VFWLSAQJLCO7NCNEEEGM/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":"2026-08-09T14:14:25Z","links":{"resolver":"https://pith.science/pith/WZO5S3VFWLSAQJLCO7NCNEEEGM","bundle":"https://pith.science/pith/WZO5S3VFWLSAQJLCO7NCNEEEGM/bundle.json","state":"https://pith.science/pith/WZO5S3VFWLSAQJLCO7NCNEEEGM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WZO5S3VFWLSAQJLCO7NCNEEEGM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:WZO5S3VFWLSAQJLCO7NCNEEEGM","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":"b1bfe6217ece81fb0033d0c0328c6aa8050c96122393866a8392822fb0e3809d","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-26T15:30:48Z","title_canon_sha256":"b5b697cc2d67749751e3277d7a306aa1cad0f3b37cce0ab7c0c40bbca96f1a1c"},"schema_version":"1.0","source":{"id":"2411.17522","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.17522","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"arxiv_version","alias_value":"2411.17522v1","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.17522","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"pith_short_12","alias_value":"WZO5S3VFWLSA","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"pith_short_16","alias_value":"WZO5S3VFWLSAQJLC","created_at":"2026-07-05T09:40:48Z"},{"alias_kind":"pith_short_8","alias_value":"WZO5S3VF","created_at":"2026-07-05T09:40:48Z"}],"graph_snapshots":[{"event_id":"sha256:d70ef8332ddafb63ee0999310757c33fbd1e74e6ef0c256eab102cebf28108e3","target":"graph","created_at":"2026-07-05T09:40:48Z","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/2411.17522/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We investigate the approximation and estimation rates of conditional diffusion transformers (DiTs) with classifier-free guidance. We present a comprehensive analysis for ``in-context'' conditional DiTs under four common data assumptions. We show that both conditional DiTs and their latent variants lead to the minimax optimality of unconditional DiTs under identified settings. Specifically, we discretize the input domains into infinitesimal grids and then perform a term-by-term Taylor expansion on the conditional diffusion score function under H\\\"older smooth data assumption. This enables fine-","authors_text":"Han Liu, Jerry Yao-Chieh Hu, Minshuo Chen, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang","cross_cats":["cs.AI","cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-26T15:30:48Z","title":"On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.17522","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":"sha256:1915dfd2e4ac1ee39374d9f074ffb868c516e20cde4a39e208aaf03a91cf93b1","target":"record","created_at":"2026-07-05T09:40:48Z","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":"b1bfe6217ece81fb0033d0c0328c6aa8050c96122393866a8392822fb0e3809d","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-26T15:30:48Z","title_canon_sha256":"b5b697cc2d67749751e3277d7a306aa1cad0f3b37cce0ab7c0c40bbca96f1a1c"},"schema_version":"1.0","source":{"id":"2411.17522","kind":"arxiv","version":1}},"canonical_sha256":"b65dd96ea5b2e408256277da2690843307072c077919be99b160b68651f0d9f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b65dd96ea5b2e408256277da2690843307072c077919be99b160b68651f0d9f3","first_computed_at":"2026-07-05T09:40:48.318299Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:40:48.318299Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7lGmP5uSbKeG4Ai69NKboiZEpHW28tIhRS8xfTNVAjpJHeYoAnWqlEwi3kidaUjPILcmGx1CtE+iy1qs23oXDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:40:48.318802Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.17522","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1915dfd2e4ac1ee39374d9f074ffb868c516e20cde4a39e208aaf03a91cf93b1","sha256:d70ef8332ddafb63ee0999310757c33fbd1e74e6ef0c256eab102cebf28108e3"],"state_sha256":"0babce4b8c60c2cd25ea4697d3f89f1647c2c47666dbe06b8453225d4493d105"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HBFeNf51EH+powRY8uEk7Cf01UplqfUJuqtAwCb8BvN2VNlgajyQ5BuRQzAnWHJpOdw97J7mQ4plUS0AKBIFDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T14:14:25.491088Z","bundle_sha256":"ce6244469e493f9c94715655624f0654017a12b4146f110c943568dde814dd10"}}