{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:NIZTTQOXTQXO4Z7YWPRDAZXATV","short_pith_number":"pith:NIZTTQOX","schema_version":"1.0","canonical_sha256":"6a3339c1d79c2eee67f8b3e23066e09d7ff706de82bc8408bc4f3746da03705a","source":{"kind":"arxiv","id":"2605.22765","version":1},"attestation_state":"computed","paper":{"title":"Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alain Durmus, Dario Shariatian, Eric Moulines, Eric P. Xing, Samson Gourevitch, Umut Simsekli, Yazid Janati","submitted_at":"2026-05-21T17:27:19Z","abstract_excerpt":"Discrete diffusion models are often trained through clean-data prediction, but the prediction can be used in different ways to define the reverse dynamics. In Masked Diffusion Models (MDM) these choices largely coincide, whereas in Uniform Diffusion Models (UDM) they do not. We show that the standard plug-in bridge parameterization for UDM is not optimized by the denoising posterior, but by a leave-one-out posterior that predicts each clean token without using its own noisy observation. This identifies a mismatch between the plug-in ELBO and the usual cross-entropy denoising objective. We char"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.22765","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-21T17:27:19Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"40c7be45576f2e7482d52822e5ab0b2018c9c735175089d2d4a65879467ceb8c","abstract_canon_sha256":"14c38d8f2fcb64a3e0c61c9bc1929b168d0cbaa3e32914708d45dcf63742fabf"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-22T02:04:54.041811Z","signature_b64":"12qwHfDcJmxsWnCo7tkv0QZmBr64gEoVzwFNCqzDA8bgTFYKIWXfnxSh4B0MGNOagh/cTEDxQxKGsTV3iKhODQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6a3339c1d79c2eee67f8b3e23066e09d7ff706de82bc8408bc4f3746da03705a","last_reissued_at":"2026-05-22T02:04:54.041352Z","signature_status":"signed_v1","first_computed_at":"2026-05-22T02:04:54.041352Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alain Durmus, Dario Shariatian, Eric Moulines, Eric P. Xing, Samson Gourevitch, Umut Simsekli, Yazid Janati","submitted_at":"2026-05-21T17:27:19Z","abstract_excerpt":"Discrete diffusion models are often trained through clean-data prediction, but the prediction can be used in different ways to define the reverse dynamics. In Masked Diffusion Models (MDM) these choices largely coincide, whereas in Uniform Diffusion Models (UDM) they do not. We show that the standard plug-in bridge parameterization for UDM is not optimized by the denoising posterior, but by a leave-one-out posterior that predicts each clean token without using its own noisy observation. This identifies a mismatch between the plug-in ELBO and the usual cross-entropy denoising objective. We char"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.22765","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/2605.22765/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.22765","created_at":"2026-05-22T02:04:54.041412+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.22765v1","created_at":"2026-05-22T02:04:54.041412+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.22765","created_at":"2026-05-22T02:04:54.041412+00:00"},{"alias_kind":"pith_short_12","alias_value":"NIZTTQOXTQXO","created_at":"2026-05-22T02:04:54.041412+00:00"},{"alias_kind":"pith_short_16","alias_value":"NIZTTQOXTQXO4Z7Y","created_at":"2026-05-22T02:04:54.041412+00:00"},{"alias_kind":"pith_short_8","alias_value":"NIZTTQOX","created_at":"2026-05-22T02:04:54.041412+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/NIZTTQOXTQXO4Z7YWPRDAZXATV","json":"https://pith.science/pith/NIZTTQOXTQXO4Z7YWPRDAZXATV.json","graph_json":"https://pith.science/api/pith-number/NIZTTQOXTQXO4Z7YWPRDAZXATV/graph.json","events_json":"https://pith.science/api/pith-number/NIZTTQOXTQXO4Z7YWPRDAZXATV/events.json","paper":"https://pith.science/paper/NIZTTQOX"},"agent_actions":{"view_html":"https://pith.science/pith/NIZTTQOXTQXO4Z7YWPRDAZXATV","download_json":"https://pith.science/pith/NIZTTQOXTQXO4Z7YWPRDAZXATV.json","view_paper":"https://pith.science/paper/NIZTTQOX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.22765&json=true","fetch_graph":"https://pith.science/api/pith-number/NIZTTQOXTQXO4Z7YWPRDAZXATV/graph.json","fetch_events":"https://pith.science/api/pith-number/NIZTTQOXTQXO4Z7YWPRDAZXATV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NIZTTQOXTQXO4Z7YWPRDAZXATV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NIZTTQOXTQXO4Z7YWPRDAZXATV/action/storage_attestation","attest_author":"https://pith.science/pith/NIZTTQOXTQXO4Z7YWPRDAZXATV/action/author_attestation","sign_citation":"https://pith.science/pith/NIZTTQOXTQXO4Z7YWPRDAZXATV/action/citation_signature","submit_replication":"https://pith.science/pith/NIZTTQOXTQXO4Z7YWPRDAZXATV/action/replication_record"}},"created_at":"2026-05-22T02:04:54.041412+00:00","updated_at":"2026-05-22T02:04:54.041412+00:00"}