{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:NYI4M4WTJOC7X2YKYQURPABICF","short_pith_number":"pith:NYI4M4WT","schema_version":"1.0","canonical_sha256":"6e11c672d34b85fbeb0ac429178028116730e971bff275b767d294cee5607cd0","source":{"kind":"arxiv","id":"2605.16239","version":1},"attestation_state":"computed","paper":{"title":"Dynamics-Level Watermarking of Flow Matching Models with Random Codes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Shuchan Wang","submitted_at":"2026-05-15T17:48:22Z","abstract_excerpt":"We introduce a dynamics-level approach to watermarking generative models. Rather than embedding signals into model weights or outputs, we embed the watermark directly into the learned continuous dynamics -- the velocity field of a flow matching model. We formulate this as random coding over a continuous channel: a key-dependent perturbation is added during training, and the message is recovered at detection time from black-box queries. The perturbation is designed to leave the generated distribution unchanged. Experiments on MNIST and CIFAR-10 across different architectures confirm reliable me"},"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":"2605.16239","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-15T17:48:22Z","cross_cats_sorted":[],"title_canon_sha256":"937d1fa2f59d5e192d32ae2cf9196075b11217614f7eaaed72850c913b99815a","abstract_canon_sha256":"3e4faa78a29dcb29530b40e815bfb4acbe12fbfeb26da48f12a209edb2a30b20"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:01:59.571249Z","signature_b64":"n37yWf+MCdn3YjwZ89kUbXmsFQPPOfaFH6uB0k0QFKKz5mZa7SmKvxXwbNG8XAyQFKrSgXnHANwB2mDswuusBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e11c672d34b85fbeb0ac429178028116730e971bff275b767d294cee5607cd0","last_reissued_at":"2026-05-20T00:01:59.570430Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:01:59.570430Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dynamics-Level Watermarking of Flow Matching Models with Random Codes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Shuchan Wang","submitted_at":"2026-05-15T17:48:22Z","abstract_excerpt":"We introduce a dynamics-level approach to watermarking generative models. Rather than embedding signals into model weights or outputs, we embed the watermark directly into the learned continuous dynamics -- the velocity field of a flow matching model. We formulate this as random coding over a continuous channel: a key-dependent perturbation is added during training, and the message is recovered at detection time from black-box queries. The perturbation is designed to leave the generated distribution unchanged. Experiments on MNIST and CIFAR-10 across different architectures confirm reliable me"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.16239","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/2605.16239/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"shingle_duplication","ran_at":"2026-05-19T17:49:42.192496Z","status":"skipped","version":"0.1.0","findings_count":0},{"name":"citation_quote_validity","ran_at":"2026-05-19T17:49:41.801177Z","status":"skipped","version":"0.1.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T17:33:23.108071Z","status":"skipped","version":"1.0.0","findings_count":0},{"name":"external_links","ran_at":"2026-05-19T17:31:26.417548Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T17:01:55.613825Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"cited_work_retraction","ran_at":"2026-05-19T16:51:57.504055Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"3cd4e344c250c8d7fa4547f5145f8fda485057d4c2907789268e349dd46a33f5"},"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":"2605.16239","created_at":"2026-05-20T00:01:59.570567+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.16239v1","created_at":"2026-05-20T00:01:59.570567+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16239","created_at":"2026-05-20T00:01:59.570567+00:00"},{"alias_kind":"pith_short_12","alias_value":"NYI4M4WTJOC7","created_at":"2026-05-20T00:01:59.570567+00:00"},{"alias_kind":"pith_short_16","alias_value":"NYI4M4WTJOC7X2YK","created_at":"2026-05-20T00:01:59.570567+00:00"},{"alias_kind":"pith_short_8","alias_value":"NYI4M4WT","created_at":"2026-05-20T00:01:59.570567+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/NYI4M4WTJOC7X2YKYQURPABICF","json":"https://pith.science/pith/NYI4M4WTJOC7X2YKYQURPABICF.json","graph_json":"https://pith.science/api/pith-number/NYI4M4WTJOC7X2YKYQURPABICF/graph.json","events_json":"https://pith.science/api/pith-number/NYI4M4WTJOC7X2YKYQURPABICF/events.json","paper":"https://pith.science/paper/NYI4M4WT"},"agent_actions":{"view_html":"https://pith.science/pith/NYI4M4WTJOC7X2YKYQURPABICF","download_json":"https://pith.science/pith/NYI4M4WTJOC7X2YKYQURPABICF.json","view_paper":"https://pith.science/paper/NYI4M4WT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.16239&json=true","fetch_graph":"https://pith.science/api/pith-number/NYI4M4WTJOC7X2YKYQURPABICF/graph.json","fetch_events":"https://pith.science/api/pith-number/NYI4M4WTJOC7X2YKYQURPABICF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NYI4M4WTJOC7X2YKYQURPABICF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NYI4M4WTJOC7X2YKYQURPABICF/action/storage_attestation","attest_author":"https://pith.science/pith/NYI4M4WTJOC7X2YKYQURPABICF/action/author_attestation","sign_citation":"https://pith.science/pith/NYI4M4WTJOC7X2YKYQURPABICF/action/citation_signature","submit_replication":"https://pith.science/pith/NYI4M4WTJOC7X2YKYQURPABICF/action/replication_record"}},"created_at":"2026-05-20T00:01:59.570567+00:00","updated_at":"2026-05-20T00:01:59.570567+00:00"}