{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LRR7GI6NM6KOFGQQT2YKPGV5OU","short_pith_number":"pith:LRR7GI6N","canonical_record":{"source":{"id":"2501.18863","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-01-31T03:10:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c0edd7cd90d4d3ec8fe62b914a35de1aed461814ea5d3e54876cb6f6f10cd735","abstract_canon_sha256":"b6aa626523edcbc62975b2f710d552fbb33354def179c2ce4716ce6d05a12ac9"},"schema_version":"1.0"},"canonical_sha256":"5c63f323cd6794e29a109eb0a79abd752387e011192ec91fce4a23e4c22d0756","source":{"kind":"arxiv","id":"2501.18863","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.18863","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"arxiv_version","alias_value":"2501.18863v1","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.18863","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"pith_short_12","alias_value":"LRR7GI6NM6KO","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"pith_short_16","alias_value":"LRR7GI6NM6KOFGQQ","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"pith_short_8","alias_value":"LRR7GI6N","created_at":"2026-07-05T10:07:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LRR7GI6NM6KOFGQQT2YKPGV5OU","target":"record","payload":{"canonical_record":{"source":{"id":"2501.18863","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-01-31T03:10:10Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c0edd7cd90d4d3ec8fe62b914a35de1aed461814ea5d3e54876cb6f6f10cd735","abstract_canon_sha256":"b6aa626523edcbc62975b2f710d552fbb33354def179c2ce4716ce6d05a12ac9"},"schema_version":"1.0"},"canonical_sha256":"5c63f323cd6794e29a109eb0a79abd752387e011192ec91fce4a23e4c22d0756","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:07:52.856976Z","signature_b64":"6e5TvnM4KKA2yR7uiiqf+qTCNlPfjeGwbQrECVlKzu14vp/h+nlh5h4O0s6YKRsrTMFZkEtsf9ZMrw1oRjFdCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5c63f323cd6794e29a109eb0a79abd752387e011192ec91fce4a23e4c22d0756","last_reissued_at":"2026-07-05T10:07:52.856490Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:07:52.856490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.18863","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":"2026-07-05T10:07:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YXK24SbJnqPHOLDkSw4xygltLZcVlRJ0Pu7V2dlQ1Wqp62jCxCDuian45zzXF+yNeuZ8gI16h9tJWIjx+HXGDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:58:58.848095Z"},"content_sha256":"fbc54a93e1dc671623090b12c2bca49ba0140b2c972bdcda0bab172e99faa394","schema_version":"1.0","event_id":"sha256:fbc54a93e1dc671623090b12c2bca49ba0140b2c972bdcda0bab172e99faa394"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LRR7GI6NM6KOFGQQT2YKPGV5OU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Jiaqi Tang, Yuling Yan","submitted_at":"2025-01-31T03:10:10Z","abstract_excerpt":"Score-based generative models, which transform noise into data by learning to reverse a diffusion process, have become a cornerstone of modern generative AI. This paper contributes to establishing theoretical guarantees for the probability flow ODE, a widely used diffusion-based sampler known for its practical efficiency. While a number of prior works address its general convergence theory, it remains unclear whether the probability flow ODE sampler can adapt to the low-dimensional structures commonly present in natural image data. We demonstrate that, with accurate score function estimation, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.18863","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/2501.18863/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":"2026-07-05T10:07:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y0EeastR4S0lY7pucgWjvoY0FEAzPwdcz5+ZuLdrJW0y9V4jDVERmbG8MbmNOxN5m0WAjIwcNe+X3OSw4CzhCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:58:58.848671Z"},"content_sha256":"2ffae4e710ed756bb3055e97b752c6da73f2a2a58593d89541676c88baf81bd2","schema_version":"1.0","event_id":"sha256:2ffae4e710ed756bb3055e97b752c6da73f2a2a58593d89541676c88baf81bd2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LRR7GI6NM6KOFGQQT2YKPGV5OU/bundle.json","state_url":"https://pith.science/pith/LRR7GI6NM6KOFGQQT2YKPGV5OU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LRR7GI6NM6KOFGQQT2YKPGV5OU/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":"2026-08-08T20:58:58Z","links":{"resolver":"https://pith.science/pith/LRR7GI6NM6KOFGQQT2YKPGV5OU","bundle":"https://pith.science/pith/LRR7GI6NM6KOFGQQT2YKPGV5OU/bundle.json","state":"https://pith.science/pith/LRR7GI6NM6KOFGQQT2YKPGV5OU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LRR7GI6NM6KOFGQQT2YKPGV5OU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LRR7GI6NM6KOFGQQT2YKPGV5OU","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":"b6aa626523edcbc62975b2f710d552fbb33354def179c2ce4716ce6d05a12ac9","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-01-31T03:10:10Z","title_canon_sha256":"c0edd7cd90d4d3ec8fe62b914a35de1aed461814ea5d3e54876cb6f6f10cd735"},"schema_version":"1.0","source":{"id":"2501.18863","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.18863","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"arxiv_version","alias_value":"2501.18863v1","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.18863","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"pith_short_12","alias_value":"LRR7GI6NM6KO","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"pith_short_16","alias_value":"LRR7GI6NM6KOFGQQ","created_at":"2026-07-05T10:07:52Z"},{"alias_kind":"pith_short_8","alias_value":"LRR7GI6N","created_at":"2026-07-05T10:07:52Z"}],"graph_snapshots":[{"event_id":"sha256:2ffae4e710ed756bb3055e97b752c6da73f2a2a58593d89541676c88baf81bd2","target":"graph","created_at":"2026-07-05T10:07:52Z","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/2501.18863/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Score-based generative models, which transform noise into data by learning to reverse a diffusion process, have become a cornerstone of modern generative AI. This paper contributes to establishing theoretical guarantees for the probability flow ODE, a widely used diffusion-based sampler known for its practical efficiency. While a number of prior works address its general convergence theory, it remains unclear whether the probability flow ODE sampler can adapt to the low-dimensional structures commonly present in natural image data. We demonstrate that, with accurate score function estimation, ","authors_text":"Jiaqi Tang, Yuling Yan","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-01-31T03:10:10Z","title":"Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.18863","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:fbc54a93e1dc671623090b12c2bca49ba0140b2c972bdcda0bab172e99faa394","target":"record","created_at":"2026-07-05T10:07:52Z","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":"b6aa626523edcbc62975b2f710d552fbb33354def179c2ce4716ce6d05a12ac9","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-01-31T03:10:10Z","title_canon_sha256":"c0edd7cd90d4d3ec8fe62b914a35de1aed461814ea5d3e54876cb6f6f10cd735"},"schema_version":"1.0","source":{"id":"2501.18863","kind":"arxiv","version":1}},"canonical_sha256":"5c63f323cd6794e29a109eb0a79abd752387e011192ec91fce4a23e4c22d0756","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5c63f323cd6794e29a109eb0a79abd752387e011192ec91fce4a23e4c22d0756","first_computed_at":"2026-07-05T10:07:52.856490Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:07:52.856490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6e5TvnM4KKA2yR7uiiqf+qTCNlPfjeGwbQrECVlKzu14vp/h+nlh5h4O0s6YKRsrTMFZkEtsf9ZMrw1oRjFdCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:07:52.856976Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.18863","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fbc54a93e1dc671623090b12c2bca49ba0140b2c972bdcda0bab172e99faa394","sha256:2ffae4e710ed756bb3055e97b752c6da73f2a2a58593d89541676c88baf81bd2"],"state_sha256":"ea795738d2347133628573613eaba9d2d25b6010d867c39614d753f32ed0cfc1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Kpt4UARg1jK3uFVKOCiu7pjCbBrWwMfJ2SgrXT2ytR+9iFj5Q508PWDj1nOE4q8BY8/okCQfqvrWWN3CoWp2CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T20:58:58.853595Z","bundle_sha256":"b9d9dfa59749984ae07c3e0fabac90b5401991d97d7aa46b6e0184d26e9bbc72"}}