{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:DF55J7BRRCN63A3QJQIODJPZS3","short_pith_number":"pith:DF55J7BR","schema_version":"1.0","canonical_sha256":"197bd4fc31889bed83704c10e1a5f996eb7bb0cfd362a87f8da514c3cac16153","source":{"kind":"arxiv","id":"2607.29235","version":1},"attestation_state":"computed","paper":{"title":"FBFM: A Training-Free Asynchronous Feedback Mechanism for Flow-Matching in World-Action Models Execution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Cong Huang, Kai Chen, Peize Li, Ruimeng Zhang, Ru Zhang, Shanghang Zhang","submitted_at":"2026-07-31T10:11:09Z","abstract_excerpt":"Although world-action models (WAMs) enhance long-horizon robot control by predicting visual evolution before acting, long-horizon reliability demands repeated re-grounding in real observations--not recursive rollout. Existing WAMs address this by refreshing history or KV cache with ground-truth data between chunks. However, such chunk-wise feedback operates at a coarse temporal granularity and thus fails to correct prediction errors at the individual time-step level. To address this, we propose Feedback Flow Matching (FBFM), a training-free inference mechanism that pushes re-grounding inside t"},"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":"2607.29235","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-31T10:11:09Z","cross_cats_sorted":["cs.AI","cs.SY","eess.SY"],"title_canon_sha256":"efe87349f5b212d1a0219983671664439ccd0d231f992deea6372cbf859e7119","abstract_canon_sha256":"ba2f9355b3f89b449c9d159cda5e9768a79009c42e7bb7f12de2d922a355d1b2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-03T01:22:25.244562Z","signature_b64":"sbkWD7+cCaOhvXwwzqDtHJy6l5l9BBbKILSYcpvbMguZOfhJ4jmJrHOCdb4LuuWELGuoqlunQiD7qUUbxZo4CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"197bd4fc31889bed83704c10e1a5f996eb7bb0cfd362a87f8da514c3cac16153","last_reissued_at":"2026-08-03T01:22:25.243065Z","signature_status":"signed_v1","first_computed_at":"2026-08-03T01:22:25.243065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FBFM: A Training-Free Asynchronous Feedback Mechanism for Flow-Matching in World-Action Models Execution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.SY","eess.SY"],"primary_cat":"cs.RO","authors_text":"Cong Huang, Kai Chen, Peize Li, Ruimeng Zhang, Ru Zhang, Shanghang Zhang","submitted_at":"2026-07-31T10:11:09Z","abstract_excerpt":"Although world-action models (WAMs) enhance long-horizon robot control by predicting visual evolution before acting, long-horizon reliability demands repeated re-grounding in real observations--not recursive rollout. Existing WAMs address this by refreshing history or KV cache with ground-truth data between chunks. However, such chunk-wise feedback operates at a coarse temporal granularity and thus fails to correct prediction errors at the individual time-step level. To address this, we propose Feedback Flow Matching (FBFM), a training-free inference mechanism that pushes re-grounding inside t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29235","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/2607.29235/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":"2607.29235","created_at":"2026-08-03T01:22:25.243996+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.29235v1","created_at":"2026-08-03T01:22:25.243996+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29235","created_at":"2026-08-03T01:22:25.243996+00:00"},{"alias_kind":"pith_short_12","alias_value":"DF55J7BRRCN6","created_at":"2026-08-03T01:22:25.243996+00:00"},{"alias_kind":"pith_short_16","alias_value":"DF55J7BRRCN63A3Q","created_at":"2026-08-03T01:22:25.243996+00:00"},{"alias_kind":"pith_short_8","alias_value":"DF55J7BR","created_at":"2026-08-03T01:22:25.243996+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/DF55J7BRRCN63A3QJQIODJPZS3","json":"https://pith.science/pith/DF55J7BRRCN63A3QJQIODJPZS3.json","graph_json":"https://pith.science/api/pith-number/DF55J7BRRCN63A3QJQIODJPZS3/graph.json","events_json":"https://pith.science/api/pith-number/DF55J7BRRCN63A3QJQIODJPZS3/events.json","paper":"https://pith.science/paper/DF55J7BR"},"agent_actions":{"view_html":"https://pith.science/pith/DF55J7BRRCN63A3QJQIODJPZS3","download_json":"https://pith.science/pith/DF55J7BRRCN63A3QJQIODJPZS3.json","view_paper":"https://pith.science/paper/DF55J7BR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.29235&json=true","fetch_graph":"https://pith.science/api/pith-number/DF55J7BRRCN63A3QJQIODJPZS3/graph.json","fetch_events":"https://pith.science/api/pith-number/DF55J7BRRCN63A3QJQIODJPZS3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DF55J7BRRCN63A3QJQIODJPZS3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DF55J7BRRCN63A3QJQIODJPZS3/action/storage_attestation","attest_author":"https://pith.science/pith/DF55J7BRRCN63A3QJQIODJPZS3/action/author_attestation","sign_citation":"https://pith.science/pith/DF55J7BRRCN63A3QJQIODJPZS3/action/citation_signature","submit_replication":"https://pith.science/pith/DF55J7BRRCN63A3QJQIODJPZS3/action/replication_record"}},"created_at":"2026-08-03T01:22:25.243996+00:00","updated_at":"2026-08-03T01:22:25.243996+00:00"}