{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:NQO77FJWAFC6KGROYDOMXYJO3B","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":"ae4c2a98ba49c4fcaa9bc53d9897d25090397f2fe0ef553c3580d1719e9e12a0","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-25T15:31:16Z","title_canon_sha256":"ca81070cca9e5d99d6df626087925de9acfab99bd600e04fdc970ba47cbbcf30"},"schema_version":"1.0","source":{"id":"2309.14394","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.14394","created_at":"2026-07-05T12:05:39Z"},{"alias_kind":"arxiv_version","alias_value":"2309.14394v2","created_at":"2026-07-05T12:05:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.14394","created_at":"2026-07-05T12:05:39Z"},{"alias_kind":"pith_short_12","alias_value":"NQO77FJWAFC6","created_at":"2026-07-05T12:05:39Z"},{"alias_kind":"pith_short_16","alias_value":"NQO77FJWAFC6KGRO","created_at":"2026-07-05T12:05:39Z"},{"alias_kind":"pith_short_8","alias_value":"NQO77FJW","created_at":"2026-07-05T12:05:39Z"}],"graph_snapshots":[{"event_id":"sha256:5439c715d5f51da8a9c7d1ee7939294529a18941234733ef92b7e18566a1b563","target":"graph","created_at":"2026-07-05T12:05:39Z","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/2309.14394/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we address the challenge of multi-domain translation, where the objective is to learn mappings between arbitrary configurations of domains within a defined set (such as $(D_1, D_2)\\rightarrow{}D_3$, $D_2\\rightarrow{}(D_1, D_3)$, $D_3\\rightarrow{}D_1$, etc. for three domains) without the need for separate models for each specific translation configuration, enabling more efficient and flexible domain translation. We introduce Multi-Domain Diffusion (MDD), a method with dual purposes: i) reconstructing any missing views for new data objects, and ii) enabling learning in semi-supervi","authors_text":"Clement Chatelain, Romain Herault, Simon Bernard, Tsiry Mayet","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-25T15:31:16Z","title":"Multiple Noises in Diffusion Model for Semi-Supervised Multi-Domain Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.14394","kind":"arxiv","version":2},"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":"sha256:904a95c66d2f075bb7fbc0a71109ac92ac62d6f7062191afcce6c9c48ec79614","target":"record","created_at":"2026-07-05T12:05:39Z","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":"ae4c2a98ba49c4fcaa9bc53d9897d25090397f2fe0ef553c3580d1719e9e12a0","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2023-09-25T15:31:16Z","title_canon_sha256":"ca81070cca9e5d99d6df626087925de9acfab99bd600e04fdc970ba47cbbcf30"},"schema_version":"1.0","source":{"id":"2309.14394","kind":"arxiv","version":2}},"canonical_sha256":"6c1dff95360145e51a2ec0dccbe12ed876321dd5c08af850a167b8c0c7244f2d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6c1dff95360145e51a2ec0dccbe12ed876321dd5c08af850a167b8c0c7244f2d","first_computed_at":"2026-07-05T12:05:39.343275Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:05:39.343275Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G0kpQvQwLJMextlzjO8Bf5avOM370m99w/wxj8qaSHj0ovo+rjbgk4yntkwe0BxDBMV66Cj3lnhzucSc2zgZAA==","signature_status":"signed_v1","signed_at":"2026-07-05T12:05:39.343687Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.14394","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:904a95c66d2f075bb7fbc0a71109ac92ac62d6f7062191afcce6c9c48ec79614","sha256:5439c715d5f51da8a9c7d1ee7939294529a18941234733ef92b7e18566a1b563"],"state_sha256":"abeae78f329c0ab27b290b4af2e0b6ca4b6a1bb531df17cc86df31995754ef62"}