{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:OTJDXGUIQOWOXABZGSMX4WVR5B","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":"5c019c832956e7b302324e3a33c180889d560bc68bd34ae14a3548e76440a5fc","cross_cats_sorted":["cs.AI","cs.CV","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-01T05:07:17Z","title_canon_sha256":"7db72a01efbaa8f094beb84903b0741533eade5265cc1ef329bf7cd4ffcaf839"},"schema_version":"1.0","source":{"id":"2310.02279","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.02279","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"arxiv_version","alias_value":"2310.02279v3","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.02279","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"pith_short_12","alias_value":"OTJDXGUIQOWO","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"pith_short_16","alias_value":"OTJDXGUIQOWOXABZ","created_at":"2026-07-05T08:02:21Z"},{"alias_kind":"pith_short_8","alias_value":"OTJDXGUI","created_at":"2026-07-05T08:02:21Z"}],"graph_snapshots":[{"event_id":"sha256:1e1fa0e6a5b857bfb270abfae660f6a8b604cea49ddc08936dc53cbc0377acb1","target":"graph","created_at":"2026-07-05T08:02:21Z","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/2310.02279/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Consistency Models (CM) (Song et al., 2023) accelerate score-based diffusion model sampling at the cost of sample quality but lack a natural way to trade-off quality for speed. To address this limitation, we propose Consistency Trajectory Model (CTM), a generalization encompassing CM and score-based models as special cases. CTM trains a single neural network that can -- in a single forward pass -- output scores (i.e., gradients of log-density) and enables unrestricted traversal between any initial and final time along the Probability Flow Ordinary Differential Equation (ODE) in a diffusion pro","authors_text":"Chieh-Hsin Lai, Dongjun Kim, Naoki Murata, Stefano Ermon, Toshimitsu Uesaka, Wei-Hsiang Liao, Yuhta Takida, Yuki Mitsufuji, Yutong He","cross_cats":["cs.AI","cs.CV","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-01T05:07:17Z","title":"Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.02279","kind":"arxiv","version":3},"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":"sha256:17fb0f32f65240eb8f6106ff87bec874efe70b559876859322c20a8b33f84778","target":"record","created_at":"2026-07-05T08:02:21Z","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":"5c019c832956e7b302324e3a33c180889d560bc68bd34ae14a3548e76440a5fc","cross_cats_sorted":["cs.AI","cs.CV","stat.ML"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-01T05:07:17Z","title_canon_sha256":"7db72a01efbaa8f094beb84903b0741533eade5265cc1ef329bf7cd4ffcaf839"},"schema_version":"1.0","source":{"id":"2310.02279","kind":"arxiv","version":3}},"canonical_sha256":"74d23b9a8883aceb803934997e5ab1e84800f27aee2a0bb99757a3c74f1241c9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"74d23b9a8883aceb803934997e5ab1e84800f27aee2a0bb99757a3c74f1241c9","first_computed_at":"2026-07-05T08:02:21.772187Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:02:21.772187Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HW6Oiv56zGWrScig3L2vSflBPUdU640Y/tGSKTXKNULVkVTx+EL2n5xm5lTHfAhBX3c9e2AEsGjLAiOpSQbTBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:02:21.772748Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.02279","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:17fb0f32f65240eb8f6106ff87bec874efe70b559876859322c20a8b33f84778","sha256:1e1fa0e6a5b857bfb270abfae660f6a8b604cea49ddc08936dc53cbc0377acb1"],"state_sha256":"0f7c2bab1fd354527fe2ec95ac54abd8a2a152a8cb35635ac29cd695d953c2bc"}