{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:U2L6AUDZRWNQUSOT7BY43NH77Z","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":"660a529c1f88d36baca135d005685631a165ebef312dbf935f09b223188c1026","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2022-06-21T19:01:19Z","title_canon_sha256":"ebb609ce2716edc2113f9535408241a9131bba3e7df127186f0e6848faff884a"},"schema_version":"1.0","source":{"id":"2206.10680","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.10680","created_at":"2026-07-05T05:06:13Z"},{"alias_kind":"arxiv_version","alias_value":"2206.10680v2","created_at":"2026-07-05T05:06:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.10680","created_at":"2026-07-05T05:06:13Z"},{"alias_kind":"pith_short_12","alias_value":"U2L6AUDZRWNQ","created_at":"2026-07-05T05:06:13Z"},{"alias_kind":"pith_short_16","alias_value":"U2L6AUDZRWNQUSOT","created_at":"2026-07-05T05:06:13Z"},{"alias_kind":"pith_short_8","alias_value":"U2L6AUDZ","created_at":"2026-07-05T05:06:13Z"}],"graph_snapshots":[{"event_id":"sha256:951af8b521b86e5ccfbf625c2ee972b72a2e77fa809a4af1026ceec884cb9802","target":"graph","created_at":"2026-07-05T05:06:13Z","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/2206.10680/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Decision-making is challenging in robotics environments with continuous object-centric states, continuous actions, long horizons, and sparse feedback. Hierarchical approaches, such as task and motion planning (TAMP), address these challenges by decomposing decision-making into two or more levels of abstraction. In a setting where demonstrations and symbolic predicates are given, prior work has shown how to learn symbolic operators and neural samplers for TAMP with manually designed parameterized policies. Our main contribution is a method for learning parameterized polices in combination with ","authors_text":"Ashay Athalye, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Tomas Lozano-Perez, Tom Silver","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2022-06-21T19:01:19Z","title":"Learning Neuro-Symbolic Skills for Bilevel Planning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.10680","kind":"arxiv","version":2},"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":"sha256:547043c2e317aa94cd41b5344348149fbf85b64fcb72b7e9fcf96dc8dc902cac","target":"record","created_at":"2026-07-05T05:06:13Z","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":"660a529c1f88d36baca135d005685631a165ebef312dbf935f09b223188c1026","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2022-06-21T19:01:19Z","title_canon_sha256":"ebb609ce2716edc2113f9535408241a9131bba3e7df127186f0e6848faff884a"},"schema_version":"1.0","source":{"id":"2206.10680","kind":"arxiv","version":2}},"canonical_sha256":"a697e050798d9b0a49d3f871cdb4fffe762ed22748cc5401327316cc4e67344a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a697e050798d9b0a49d3f871cdb4fffe762ed22748cc5401327316cc4e67344a","first_computed_at":"2026-07-05T05:06:13.232931Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:06:13.232931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pwLExZJSgPMF5QO1DTnZBzIYyIQCrpVIkZmC9vsHHhzvU772HBCZgFcsvNIQCA3kO6dEHyeGKznEEfkCFPrUCg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:06:13.233505Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.10680","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:547043c2e317aa94cd41b5344348149fbf85b64fcb72b7e9fcf96dc8dc902cac","sha256:951af8b521b86e5ccfbf625c2ee972b72a2e77fa809a4af1026ceec884cb9802"],"state_sha256":"62aa60733565eccd8173fbd5cbf8733d411c9af7c3d2d63400be1255b01d3711"}