{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:BL6HZCKTXDXUWNOX6ORB6JGBWT","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":"fb94df573b8c9dfe92cab5116a6296c1c93405fd5027fd713e9dd860a054c744","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-09-02T15:20:36Z","title_canon_sha256":"be653ed874160ea416b33892f82250c72767c11aca4d393a3be9e5b3db21813d"},"schema_version":"1.0","source":{"id":"2309.00966","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.00966","created_at":"2026-07-05T06:47:30Z"},{"alias_kind":"arxiv_version","alias_value":"2309.00966v1","created_at":"2026-07-05T06:47:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.00966","created_at":"2026-07-05T06:47:30Z"},{"alias_kind":"pith_short_12","alias_value":"BL6HZCKTXDXU","created_at":"2026-07-05T06:47:30Z"},{"alias_kind":"pith_short_16","alias_value":"BL6HZCKTXDXUWNOX","created_at":"2026-07-05T06:47:30Z"},{"alias_kind":"pith_short_8","alias_value":"BL6HZCKT","created_at":"2026-07-05T06:47:30Z"}],"graph_snapshots":[{"event_id":"sha256:8b7ed4c2b16494b67926af499d003dc8e8c66ea388450d78fa9b6512d9760756","target":"graph","created_at":"2026-07-05T06:47:30Z","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/2309.00966/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces an approach for learning to solve continuous constraint satisfaction problems (CCSP) in robotic reasoning and planning. Previous methods primarily rely on hand-engineering or learning generators for specific constraint types and then rejecting the value assignments when other constraints are violated. By contrast, our model, the compositional diffusion continuous constraint solver (Diffusion-CCSP) derives global solutions to CCSPs by representing them as factor graphs and combining the energies of diffusion models trained to sample for individual constraint types. Diffusi","authors_text":"Jiajun Wu, Jiayuan Mao, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Tom\\'as Lozano-P\\'erez, Yilun Du, Zhutian Yang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-09-02T15:20:36Z","title":"Compositional Diffusion-Based Continuous Constraint Solvers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.00966","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":"sha256:386810b1fe892c3326df4857f0977a48a20ce2cab7ea3b2f848e5f8ba3f7205d","target":"record","created_at":"2026-07-05T06:47:30Z","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":"fb94df573b8c9dfe92cab5116a6296c1c93405fd5027fd713e9dd860a054c744","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-09-02T15:20:36Z","title_canon_sha256":"be653ed874160ea416b33892f82250c72767c11aca4d393a3be9e5b3db21813d"},"schema_version":"1.0","source":{"id":"2309.00966","kind":"arxiv","version":1}},"canonical_sha256":"0afc7c8953b8ef4b35d7f3a21f24c1b4ef244ec4d70d1cb6e581825c5a2a1380","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0afc7c8953b8ef4b35d7f3a21f24c1b4ef244ec4d70d1cb6e581825c5a2a1380","first_computed_at":"2026-07-05T06:47:30.306495Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:47:30.306495Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VA9ibyaJ2Q1gLjbRgBO1hY23+1kslcA77bPB3gAz9VL1LCTonGe1m3IVD0Smv0RtoIUM1aPQRSFRW5V2tK6VDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:47:30.306974Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.00966","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:386810b1fe892c3326df4857f0977a48a20ce2cab7ea3b2f848e5f8ba3f7205d","sha256:8b7ed4c2b16494b67926af499d003dc8e8c66ea388450d78fa9b6512d9760756"],"state_sha256":"30db015d7fa4b620f29339e6df2ea110c054b125196c8e718a2efcdb5c371a0b"}