{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:FJONDMM6M7OJ5TJN5A4BDWDBOC","short_pith_number":"pith:FJONDMM6","canonical_record":{"source":{"id":"2412.07544","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-10T14:28:18Z","cross_cats_sorted":["cs.RO","stat.ML"],"title_canon_sha256":"52e9341917068aa0e1d0fd8299f6c615d92bb23c1467abc5e0d01036fb9f4236","abstract_canon_sha256":"8a2850d7d7b649f14ea8dc4cddb7bda3bd0078304987100ebf0ebed4dda70a7e"},"schema_version":"1.0"},"canonical_sha256":"2a5cd1b19e67dc9ecd2de83811d86170b7ced37501efa80ddcc302cb0756e379","source":{"kind":"arxiv","id":"2412.07544","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.07544","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"arxiv_version","alias_value":"2412.07544v2","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.07544","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"pith_short_12","alias_value":"FJONDMM6M7OJ","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"pith_short_16","alias_value":"FJONDMM6M7OJ5TJN","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"pith_short_8","alias_value":"FJONDMM6","created_at":"2026-07-05T10:39:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:FJONDMM6M7OJ5TJN5A4BDWDBOC","target":"record","payload":{"canonical_record":{"source":{"id":"2412.07544","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-10T14:28:18Z","cross_cats_sorted":["cs.RO","stat.ML"],"title_canon_sha256":"52e9341917068aa0e1d0fd8299f6c615d92bb23c1467abc5e0d01036fb9f4236","abstract_canon_sha256":"8a2850d7d7b649f14ea8dc4cddb7bda3bd0078304987100ebf0ebed4dda70a7e"},"schema_version":"1.0"},"canonical_sha256":"2a5cd1b19e67dc9ecd2de83811d86170b7ced37501efa80ddcc302cb0756e379","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:39:24.323943Z","signature_b64":"kNbAtLXV6/mcJLCu2lX15i/8pXZXswHcM57iopl18T2vbdHQOchxd7nUOAZ6L2jHwI3C3c4+euJgxAItj3gaAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2a5cd1b19e67dc9ecd2de83811d86170b7ced37501efa80ddcc302cb0756e379","last_reissued_at":"2026-07-05T10:39:24.323406Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:39:24.323406Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.07544","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:39:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SMgw1g3b6Lts2cO4i2R3bFZDy4heohUVMZnYye3FS5ORQgyTSZ99rVA883iZMAv5kIxOeeGi3Jlgm3l9LjzqDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:18:53.586570Z"},"content_sha256":"523cf54528fb16feb630b2c9061352931db3b4c88b431689805480af877a83c2","schema_version":"1.0","event_id":"sha256:523cf54528fb16feb630b2c9061352931db3b4c88b431689805480af877a83c2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:FJONDMM6M7OJ5TJN5A4BDWDBOC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO","stat.ML"],"primary_cat":"cs.LG","authors_text":"Amin Abyaneh, Giancarlo Ferrari-Trecate, Hsiu-Chin Lin, Mahrokh G. Boroujeni","submitted_at":"2024-12-10T14:28:18Z","abstract_excerpt":"Imitation learning is a data-driven approach to learning policies from expert behavior, but it is prone to unreliable outcomes in out-of-sample (OOS) regions. While previous research relying on stable dynamical systems guarantees convergence to a desired state, it often overlooks transient behavior. We propose a framework for learning policies modeled by contractive dynamical systems, ensuring that all policy rollouts converge regardless of perturbations, and in turn, enable efficient OOS recovery. By leveraging recurrent equilibrium networks and coupling layers, the policy structure guarantee"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.07544","kind":"arxiv","version":2},"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/2412.07544/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:39:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OxCzRPf/rzGtPFwklzhGvMcC2+KmH5fp1IBV7cCip8wMN+vZ4BbD/AmG2MQRRxbU2S0yGg5purEAKQXZGQ2TDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:18:53.587439Z"},"content_sha256":"f88e212acbfb255bb325a0af394930814d1a019f9f43deb6bd5102100c281bc9","schema_version":"1.0","event_id":"sha256:f88e212acbfb255bb325a0af394930814d1a019f9f43deb6bd5102100c281bc9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FJONDMM6M7OJ5TJN5A4BDWDBOC/bundle.json","state_url":"https://pith.science/pith/FJONDMM6M7OJ5TJN5A4BDWDBOC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FJONDMM6M7OJ5TJN5A4BDWDBOC/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-14T08:18:53Z","links":{"resolver":"https://pith.science/pith/FJONDMM6M7OJ5TJN5A4BDWDBOC","bundle":"https://pith.science/pith/FJONDMM6M7OJ5TJN5A4BDWDBOC/bundle.json","state":"https://pith.science/pith/FJONDMM6M7OJ5TJN5A4BDWDBOC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FJONDMM6M7OJ5TJN5A4BDWDBOC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FJONDMM6M7OJ5TJN5A4BDWDBOC","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":"8a2850d7d7b649f14ea8dc4cddb7bda3bd0078304987100ebf0ebed4dda70a7e","cross_cats_sorted":["cs.RO","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-10T14:28:18Z","title_canon_sha256":"52e9341917068aa0e1d0fd8299f6c615d92bb23c1467abc5e0d01036fb9f4236"},"schema_version":"1.0","source":{"id":"2412.07544","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.07544","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"arxiv_version","alias_value":"2412.07544v2","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.07544","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"pith_short_12","alias_value":"FJONDMM6M7OJ","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"pith_short_16","alias_value":"FJONDMM6M7OJ5TJN","created_at":"2026-07-05T10:39:24Z"},{"alias_kind":"pith_short_8","alias_value":"FJONDMM6","created_at":"2026-07-05T10:39:24Z"}],"graph_snapshots":[{"event_id":"sha256:f88e212acbfb255bb325a0af394930814d1a019f9f43deb6bd5102100c281bc9","target":"graph","created_at":"2026-07-05T10:39:24Z","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/2412.07544/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Imitation learning is a data-driven approach to learning policies from expert behavior, but it is prone to unreliable outcomes in out-of-sample (OOS) regions. While previous research relying on stable dynamical systems guarantees convergence to a desired state, it often overlooks transient behavior. We propose a framework for learning policies modeled by contractive dynamical systems, ensuring that all policy rollouts converge regardless of perturbations, and in turn, enable efficient OOS recovery. By leveraging recurrent equilibrium networks and coupling layers, the policy structure guarantee","authors_text":"Amin Abyaneh, Giancarlo Ferrari-Trecate, Hsiu-Chin Lin, Mahrokh G. Boroujeni","cross_cats":["cs.RO","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-10T14:28:18Z","title":"Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.07544","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":"sha256:523cf54528fb16feb630b2c9061352931db3b4c88b431689805480af877a83c2","target":"record","created_at":"2026-07-05T10:39:24Z","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":"8a2850d7d7b649f14ea8dc4cddb7bda3bd0078304987100ebf0ebed4dda70a7e","cross_cats_sorted":["cs.RO","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-10T14:28:18Z","title_canon_sha256":"52e9341917068aa0e1d0fd8299f6c615d92bb23c1467abc5e0d01036fb9f4236"},"schema_version":"1.0","source":{"id":"2412.07544","kind":"arxiv","version":2}},"canonical_sha256":"2a5cd1b19e67dc9ecd2de83811d86170b7ced37501efa80ddcc302cb0756e379","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2a5cd1b19e67dc9ecd2de83811d86170b7ced37501efa80ddcc302cb0756e379","first_computed_at":"2026-07-05T10:39:24.323406Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:39:24.323406Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kNbAtLXV6/mcJLCu2lX15i/8pXZXswHcM57iopl18T2vbdHQOchxd7nUOAZ6L2jHwI3C3c4+euJgxAItj3gaAg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:39:24.323943Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.07544","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:523cf54528fb16feb630b2c9061352931db3b4c88b431689805480af877a83c2","sha256:f88e212acbfb255bb325a0af394930814d1a019f9f43deb6bd5102100c281bc9"],"state_sha256":"d4f49eaf202cb48a2cfdd25319e0ff9f91558e49ec2b9cf33a05e895b24b9392"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yZqBhUJhCN5tX3YFeQnXNwrQ4J0AJILm9gPUY8ReoRB+Ks9nAcc9skPiLdbpmvYnV4SmYX/6BDxGcysyzN7RAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T08:18:53.594789Z","bundle_sha256":"41c28a4c19ed29fecf0654b09e5ba93ee419ed1e5fa45f9378bbbb0e2a8856e4"}}