{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RMC646UYLLESYX5BBVTBXEXCW4","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":"f954e2244ee9615af2d5dcec17493cabc545eb8b91ce6dfaff2430bbbf8bd73c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-09T06:32:26Z","title_canon_sha256":"548f082134a67c2305b644b4bd2716f2b84e27442d15da2b41a7fbaa1a48234c"},"schema_version":"1.0","source":{"id":"2410.07273","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.07273","created_at":"2026-07-05T09:18:33Z"},{"alias_kind":"arxiv_version","alias_value":"2410.07273v1","created_at":"2026-07-05T09:18:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.07273","created_at":"2026-07-05T09:18:33Z"},{"alias_kind":"pith_short_12","alias_value":"RMC646UYLLES","created_at":"2026-07-05T09:18:33Z"},{"alias_kind":"pith_short_16","alias_value":"RMC646UYLLESYX5B","created_at":"2026-07-05T09:18:33Z"},{"alias_kind":"pith_short_8","alias_value":"RMC646UY","created_at":"2026-07-05T09:18:33Z"}],"graph_snapshots":[{"event_id":"sha256:8202e8f505ae57e01c7937819eca33676704eb96b04df449d09cc01c3a1ad0d6","target":"graph","created_at":"2026-07-05T09:18:33Z","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/2410.07273/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The inversion of diffusion model sampling, which aims to find the corresponding initial noise of a sample, plays a critical role in various tasks. Recently, several heuristic exact inversion samplers have been proposed to address the inexact inversion issue in a training-free manner. However, the theoretical properties of these heuristic samplers remain unknown and they often exhibit mediocre sampling quality. In this paper, we introduce a generic formulation, \\emph{Bidirectional Explicit Linear Multi-step} (BELM) samplers, of the exact inversion samplers, which includes all previously propose","authors_text":"Chao Zhang, Chen Li, Fangyikang Wang, Hanbin Zhao, Hubery Yin, Hui Qian, Huminhao Zhu, Yuejiang Dong","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-09T06:32:26Z","title":"BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.07273","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":"sha256:9c8b416842c356094d259da71ed54f873ac707241e30195f7cdbd09579acefb7","target":"record","created_at":"2026-07-05T09:18:33Z","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":"f954e2244ee9615af2d5dcec17493cabc545eb8b91ce6dfaff2430bbbf8bd73c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-09T06:32:26Z","title_canon_sha256":"548f082134a67c2305b644b4bd2716f2b84e27442d15da2b41a7fbaa1a48234c"},"schema_version":"1.0","source":{"id":"2410.07273","kind":"arxiv","version":1}},"canonical_sha256":"8b05ee7a985ac92c5fa10d661b92e2b7376d8b411cb42f51a34b1c70c91fd4c8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8b05ee7a985ac92c5fa10d661b92e2b7376d8b411cb42f51a34b1c70c91fd4c8","first_computed_at":"2026-07-05T09:18:33.869708Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:18:33.869708Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fKO+RCU9lQsISlVbaWMkBzKUOE5Ws0CbLf/3vODWJrQ4w9NHLugb5zjs0vX+R//vOOmlIL3v0Kyt+trKMogxCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:18:33.870197Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.07273","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9c8b416842c356094d259da71ed54f873ac707241e30195f7cdbd09579acefb7","sha256:8202e8f505ae57e01c7937819eca33676704eb96b04df449d09cc01c3a1ad0d6"],"state_sha256":"6ea7f28a62eb98bc2febb572506f86f87f75ca634343bb0f4ea9def9c4862504"}