{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:RSQTYLRLBJV7XY24AFFPG4ZDND","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":"eec4238874ecb7016559703d7ed71638272d6caef6b125da2ed9e1b6859b36a2","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-19T17:36:54Z","title_canon_sha256":"2ff8316408b0eb5c820815f50c0e6e0a5e587e59783c7dccf5b6e62432cabb78"},"schema_version":"1.0","source":{"id":"2503.15457","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.15457","created_at":"2026-07-05T10:35:26Z"},{"alias_kind":"arxiv_version","alias_value":"2503.15457v1","created_at":"2026-07-05T10:35:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.15457","created_at":"2026-07-05T10:35:26Z"},{"alias_kind":"pith_short_12","alias_value":"RSQTYLRLBJV7","created_at":"2026-07-05T10:35:26Z"},{"alias_kind":"pith_short_16","alias_value":"RSQTYLRLBJV7XY24","created_at":"2026-07-05T10:35:26Z"},{"alias_kind":"pith_short_8","alias_value":"RSQTYLRL","created_at":"2026-07-05T10:35:26Z"}],"graph_snapshots":[{"event_id":"sha256:2a59eaffbfb71ee338a8c7fe611d40994aeea9d1dad7ce716cbf2a5eca95bebc","target":"graph","created_at":"2026-07-05T10:35:26Z","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/2503.15457/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Masked Diffusion Models (MDMs) have emerged as a powerful generative modeling technique. Despite their remarkable results, they typically suffer from slow inference with several steps. In this paper, we propose Di$\\mathtt{[M]}$O, a novel approach that distills masked diffusion models into a one-step generator. Di$\\mathtt{[M]}$O addresses two key challenges: (1) the intractability of using intermediate-step information for one-step generation, which we solve through token-level distribution matching that optimizes model output logits by an 'on-policy framework' with the help of an auxiliary mod","authors_text":"St\\'ephane Lathuili\\`ere, Vicky Kalogeiton, Xi Wang, Yuanzhi Zhu","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-19T17:36:54Z","title":"Di$\\mathtt{[M]}$O: Distilling Masked Diffusion Models into One-step Generator"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.15457","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":"sha256:040b07a3a880a0bfa2a284759fc0343839ecefeb0b08e0ca150ed79f44f28588","target":"record","created_at":"2026-07-05T10:35:26Z","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":"eec4238874ecb7016559703d7ed71638272d6caef6b125da2ed9e1b6859b36a2","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-19T17:36:54Z","title_canon_sha256":"2ff8316408b0eb5c820815f50c0e6e0a5e587e59783c7dccf5b6e62432cabb78"},"schema_version":"1.0","source":{"id":"2503.15457","kind":"arxiv","version":1}},"canonical_sha256":"8ca13c2e2b0a6bfbe35c014af3732368c9aaf9e28d74be82b22d1faf3a9509c0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8ca13c2e2b0a6bfbe35c014af3732368c9aaf9e28d74be82b22d1faf3a9509c0","first_computed_at":"2026-07-05T10:35:26.634262Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:35:26.634262Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AV4zjaSjHmPICuS5TEKnH4wQrBiPwQAqzCP/f8hLopHSD4EtwlqU3PgzJhDLVjDz8ZmxPtEM/ALL3MabUVJWDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:35:26.635202Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.15457","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:040b07a3a880a0bfa2a284759fc0343839ecefeb0b08e0ca150ed79f44f28588","sha256:2a59eaffbfb71ee338a8c7fe611d40994aeea9d1dad7ce716cbf2a5eca95bebc"],"state_sha256":"1d41e4cfa6a13ce9551e81fe20e44113c954c4ba429ed8afd8dbe1250d14b7ad"}