{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:5L37CWL77LF53ITZRCJVVODCBH","short_pith_number":"pith:5L37CWL7","canonical_record":{"source":{"id":"2403.12585","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-19T09:47:08Z","cross_cats_sorted":[],"title_canon_sha256":"3ad9537a971e383cfbf922965c567c87fea8cd104aae55c7523ca54702145380","abstract_canon_sha256":"e3ddf47a439a8b7505b11811454f24b29c90d529e12788ed0e79e35eeca29222"},"schema_version":"1.0"},"canonical_sha256":"eaf7f1597ffacbdda27988935ab86209cd9171bcb4c41dcbcc140c8c4a8bc445","source":{"kind":"arxiv","id":"2403.12585","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.12585","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"arxiv_version","alias_value":"2403.12585v1","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.12585","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"pith_short_12","alias_value":"5L37CWL77LF5","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"pith_short_16","alias_value":"5L37CWL77LF53ITZ","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"pith_short_8","alias_value":"5L37CWL7","created_at":"2026-07-05T07:58:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:5L37CWL77LF53ITZRCJVVODCBH","target":"record","payload":{"canonical_record":{"source":{"id":"2403.12585","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-19T09:47:08Z","cross_cats_sorted":[],"title_canon_sha256":"3ad9537a971e383cfbf922965c567c87fea8cd104aae55c7523ca54702145380","abstract_canon_sha256":"e3ddf47a439a8b7505b11811454f24b29c90d529e12788ed0e79e35eeca29222"},"schema_version":"1.0"},"canonical_sha256":"eaf7f1597ffacbdda27988935ab86209cd9171bcb4c41dcbcc140c8c4a8bc445","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:58:04.158683Z","signature_b64":"bVyj03ThESbxMRJ7ScEoGB6pxPZeR0RTZfJ+A+57C0oSbk9ROoUxhAjxSmFWOloeREZBn2PdquaZPW/pnEXhBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eaf7f1597ffacbdda27988935ab86209cd9171bcb4c41dcbcc140c8c4a8bc445","last_reissued_at":"2026-07-05T07:58:04.158163Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:58:04.158163Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.12585","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":"2026-07-05T07:58:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hDi02ZoDTk4wE8XOxcfdILBvRVFh4GOsoZyu3pguxdpBIykyi0/1SdfZTUzRo0dQZi3m4iAQdtMTDRRb7NzlCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:19:48.782549Z"},"content_sha256":"607b32119e5ecf01fdeb9ebddd297c4eda5d98d600350f40c9924ccb1adc0025","schema_version":"1.0","event_id":"sha256:607b32119e5ecf01fdeb9ebddd297c4eda5d98d600350f40c9924ccb1adc0025"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:5L37CWL77LF53ITZRCJVVODCBH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LASPA: Latent Spatial Alignment for Fast Training-free Single Image Editing","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Peter Wonka, Yazeed Alharbi","submitted_at":"2024-03-19T09:47:08Z","abstract_excerpt":"We present a novel, training-free approach for textual editing of real images using diffusion models. Unlike prior methods that rely on computationally expensive finetuning, our approach leverages LAtent SPatial Alignment (LASPA) to efficiently preserve image details. We demonstrate how the diffusion process is amenable to spatial guidance using a reference image, leading to semantically coherent edits. This eliminates the need for complex optimization and costly model finetuning, resulting in significantly faster editing compared to previous methods. Additionally, our method avoids the storag"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.12585","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/2403.12585/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":"2026-07-05T07:58:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"05Tw6KXsooWydOUjzD/wshSS0ExpMPB3ds+sAgJCUpyCBgzRCktcIpKMMofn0w29oggZusD0fuadtAyNhWTPDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:19:48.783684Z"},"content_sha256":"023d63f6f7ba57d038f6e7d5c0986c6df810594abe8c481743124b1b2acd3bee","schema_version":"1.0","event_id":"sha256:023d63f6f7ba57d038f6e7d5c0986c6df810594abe8c481743124b1b2acd3bee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5L37CWL77LF53ITZRCJVVODCBH/bundle.json","state_url":"https://pith.science/pith/5L37CWL77LF53ITZRCJVVODCBH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5L37CWL77LF53ITZRCJVVODCBH/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":"2026-08-09T13:19:48Z","links":{"resolver":"https://pith.science/pith/5L37CWL77LF53ITZRCJVVODCBH","bundle":"https://pith.science/pith/5L37CWL77LF53ITZRCJVVODCBH/bundle.json","state":"https://pith.science/pith/5L37CWL77LF53ITZRCJVVODCBH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5L37CWL77LF53ITZRCJVVODCBH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5L37CWL77LF53ITZRCJVVODCBH","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":"e3ddf47a439a8b7505b11811454f24b29c90d529e12788ed0e79e35eeca29222","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-19T09:47:08Z","title_canon_sha256":"3ad9537a971e383cfbf922965c567c87fea8cd104aae55c7523ca54702145380"},"schema_version":"1.0","source":{"id":"2403.12585","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.12585","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"arxiv_version","alias_value":"2403.12585v1","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.12585","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"pith_short_12","alias_value":"5L37CWL77LF5","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"pith_short_16","alias_value":"5L37CWL77LF53ITZ","created_at":"2026-07-05T07:58:04Z"},{"alias_kind":"pith_short_8","alias_value":"5L37CWL7","created_at":"2026-07-05T07:58:04Z"}],"graph_snapshots":[{"event_id":"sha256:023d63f6f7ba57d038f6e7d5c0986c6df810594abe8c481743124b1b2acd3bee","target":"graph","created_at":"2026-07-05T07:58:04Z","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/2403.12585/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a novel, training-free approach for textual editing of real images using diffusion models. Unlike prior methods that rely on computationally expensive finetuning, our approach leverages LAtent SPatial Alignment (LASPA) to efficiently preserve image details. We demonstrate how the diffusion process is amenable to spatial guidance using a reference image, leading to semantically coherent edits. This eliminates the need for complex optimization and costly model finetuning, resulting in significantly faster editing compared to previous methods. Additionally, our method avoids the storag","authors_text":"Peter Wonka, Yazeed Alharbi","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-19T09:47:08Z","title":"LASPA: Latent Spatial Alignment for Fast Training-free Single Image Editing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.12585","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":"sha256:607b32119e5ecf01fdeb9ebddd297c4eda5d98d600350f40c9924ccb1adc0025","target":"record","created_at":"2026-07-05T07:58:04Z","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":"e3ddf47a439a8b7505b11811454f24b29c90d529e12788ed0e79e35eeca29222","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-19T09:47:08Z","title_canon_sha256":"3ad9537a971e383cfbf922965c567c87fea8cd104aae55c7523ca54702145380"},"schema_version":"1.0","source":{"id":"2403.12585","kind":"arxiv","version":1}},"canonical_sha256":"eaf7f1597ffacbdda27988935ab86209cd9171bcb4c41dcbcc140c8c4a8bc445","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eaf7f1597ffacbdda27988935ab86209cd9171bcb4c41dcbcc140c8c4a8bc445","first_computed_at":"2026-07-05T07:58:04.158163Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:58:04.158163Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bVyj03ThESbxMRJ7ScEoGB6pxPZeR0RTZfJ+A+57C0oSbk9ROoUxhAjxSmFWOloeREZBn2PdquaZPW/pnEXhBw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:58:04.158683Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.12585","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:607b32119e5ecf01fdeb9ebddd297c4eda5d98d600350f40c9924ccb1adc0025","sha256:023d63f6f7ba57d038f6e7d5c0986c6df810594abe8c481743124b1b2acd3bee"],"state_sha256":"66d7d837a3a8460e89786cb801bdaac7a611bd51a3ebd241e22def709158d478"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7S4Mi2R4IV8FmWKAIG40quwuKE3Uu9dpnuqaYD7adkrNqjeYIRH0ImheJn8YrlAOZHDXfvcr6NA4hxYi485PDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T13:19:48.789613Z","bundle_sha256":"1bcf5efd2a2404cf7a18f417bc20a8cb0c2597b536bc3b2482ed754382187f45"}}