{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:LMM63Y4PV5LKJSGWCRRAE4GCAY","short_pith_number":"pith:LMM63Y4P","canonical_record":{"source":{"id":"2302.02788","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-06T14:03:33Z","cross_cats_sorted":[],"title_canon_sha256":"537ca193a78b21f0765ca1edaa0b55bfc8222b2c62721b4ba052e5d92a216d1d","abstract_canon_sha256":"ca880c1bdf168582edcb05465252da7854721485cbe4d00ec24406007e9b1c81"},"schema_version":"1.0"},"canonical_sha256":"5b19ede38faf56a4c8d614620270c2060ddeb9397275be3f407db444e51a37f5","source":{"kind":"arxiv","id":"2302.02788","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.02788","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"arxiv_version","alias_value":"2302.02788v1","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.02788","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"pith_short_12","alias_value":"LMM63Y4PV5LK","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"pith_short_16","alias_value":"LMM63Y4PV5LKJSGW","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"pith_short_8","alias_value":"LMM63Y4P","created_at":"2026-07-05T05:39:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:LMM63Y4PV5LKJSGWCRRAE4GCAY","target":"record","payload":{"canonical_record":{"source":{"id":"2302.02788","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-06T14:03:33Z","cross_cats_sorted":[],"title_canon_sha256":"537ca193a78b21f0765ca1edaa0b55bfc8222b2c62721b4ba052e5d92a216d1d","abstract_canon_sha256":"ca880c1bdf168582edcb05465252da7854721485cbe4d00ec24406007e9b1c81"},"schema_version":"1.0"},"canonical_sha256":"5b19ede38faf56a4c8d614620270c2060ddeb9397275be3f407db444e51a37f5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:39:06.717692Z","signature_b64":"1JLen6im76nxKfL5Q4W+rA1wJ0b9ABfRIV6n0FXR+L/bOU80wMttyH+6nNrd7yjWatKcW82wyHAkaxZzlmqjAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5b19ede38faf56a4c8d614620270c2060ddeb9397275be3f407db444e51a37f5","last_reissued_at":"2026-07-05T05:39:06.717325Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:39:06.717325Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.02788","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:39:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5OJCyawOkb6bwkrXQAMRqOorwrJoi+0H20g83M9gOdCRwsxH7u9yK2A6dsak8JDL17CQEwyCmya+sHHhQ85JDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T09:34:13.963596Z"},"content_sha256":"cb8476126131682351a2dc92895a3177e00656191326f267ccce83ccdb3e80be","schema_version":"1.0","event_id":"sha256:cb8476126131682351a2dc92895a3177e00656191326f267ccce83ccdb3e80be"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:LMM63Y4PV5LKJSGWCRRAE4GCAY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Strong Baseline for Batch Imitation Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Kamil Ciosek, Lucas Maystre, Matthew Smith, Zhenwen Dai","submitted_at":"2023-02-06T14:03:33Z","abstract_excerpt":"Imitation of expert behaviour is a highly desirable and safe approach to the problem of sequential decision making. We provide an easy-to-implement, novel algorithm for imitation learning under a strict data paradigm, in which the agent must learn solely from data collected a priori. This paradigm allows our algorithm to be used for environments in which safety or cost are of critical concern. Our algorithm requires no additional hyper-parameter tuning beyond any standard batch reinforcement learning (RL) algorithm, making it an ideal baseline for such data-strict regimes. Furthermore, we prov"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.02788","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/2302.02788/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":"2026-07-05T05:39:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rGBJSu23MCV5rs2DaB2DgZKXES3uGB1SSNxrMhFZYXfxvFzrJjjUt3xPY5aOjN7Rf4q45BqWwycMs/izOI9uBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T09:34:13.964096Z"},"content_sha256":"339a11cd25772136aa908293203c29030fad71e1682dfe391e87c066ded9a384","schema_version":"1.0","event_id":"sha256:339a11cd25772136aa908293203c29030fad71e1682dfe391e87c066ded9a384"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LMM63Y4PV5LKJSGWCRRAE4GCAY/bundle.json","state_url":"https://pith.science/pith/LMM63Y4PV5LKJSGWCRRAE4GCAY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LMM63Y4PV5LKJSGWCRRAE4GCAY/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":"2026-08-08T09:34:13Z","links":{"resolver":"https://pith.science/pith/LMM63Y4PV5LKJSGWCRRAE4GCAY","bundle":"https://pith.science/pith/LMM63Y4PV5LKJSGWCRRAE4GCAY/bundle.json","state":"https://pith.science/pith/LMM63Y4PV5LKJSGWCRRAE4GCAY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LMM63Y4PV5LKJSGWCRRAE4GCAY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:LMM63Y4PV5LKJSGWCRRAE4GCAY","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":"ca880c1bdf168582edcb05465252da7854721485cbe4d00ec24406007e9b1c81","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-06T14:03:33Z","title_canon_sha256":"537ca193a78b21f0765ca1edaa0b55bfc8222b2c62721b4ba052e5d92a216d1d"},"schema_version":"1.0","source":{"id":"2302.02788","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.02788","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"arxiv_version","alias_value":"2302.02788v1","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.02788","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"pith_short_12","alias_value":"LMM63Y4PV5LK","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"pith_short_16","alias_value":"LMM63Y4PV5LKJSGW","created_at":"2026-07-05T05:39:06Z"},{"alias_kind":"pith_short_8","alias_value":"LMM63Y4P","created_at":"2026-07-05T05:39:06Z"}],"graph_snapshots":[{"event_id":"sha256:339a11cd25772136aa908293203c29030fad71e1682dfe391e87c066ded9a384","target":"graph","created_at":"2026-07-05T05:39:06Z","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/2302.02788/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Imitation of expert behaviour is a highly desirable and safe approach to the problem of sequential decision making. We provide an easy-to-implement, novel algorithm for imitation learning under a strict data paradigm, in which the agent must learn solely from data collected a priori. This paradigm allows our algorithm to be used for environments in which safety or cost are of critical concern. Our algorithm requires no additional hyper-parameter tuning beyond any standard batch reinforcement learning (RL) algorithm, making it an ideal baseline for such data-strict regimes. Furthermore, we prov","authors_text":"Kamil Ciosek, Lucas Maystre, Matthew Smith, Zhenwen Dai","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-06T14:03:33Z","title":"A Strong Baseline for Batch Imitation Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.02788","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:cb8476126131682351a2dc92895a3177e00656191326f267ccce83ccdb3e80be","target":"record","created_at":"2026-07-05T05:39:06Z","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":"ca880c1bdf168582edcb05465252da7854721485cbe4d00ec24406007e9b1c81","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-06T14:03:33Z","title_canon_sha256":"537ca193a78b21f0765ca1edaa0b55bfc8222b2c62721b4ba052e5d92a216d1d"},"schema_version":"1.0","source":{"id":"2302.02788","kind":"arxiv","version":1}},"canonical_sha256":"5b19ede38faf56a4c8d614620270c2060ddeb9397275be3f407db444e51a37f5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5b19ede38faf56a4c8d614620270c2060ddeb9397275be3f407db444e51a37f5","first_computed_at":"2026-07-05T05:39:06.717325Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:39:06.717325Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1JLen6im76nxKfL5Q4W+rA1wJ0b9ABfRIV6n0FXR+L/bOU80wMttyH+6nNrd7yjWatKcW82wyHAkaxZzlmqjAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:39:06.717692Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.02788","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cb8476126131682351a2dc92895a3177e00656191326f267ccce83ccdb3e80be","sha256:339a11cd25772136aa908293203c29030fad71e1682dfe391e87c066ded9a384"],"state_sha256":"a0e89f6aa52716047561202d07f311d12c3abdb6ef619523d49635ae96324542"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dDPKBe/Hf4/0QVYuOr0nAcMQluurzCgIXUEVyWaMatJspiNOtlnbnmduS8n9iw6J2HIVwV0q9ymnXiOS5ratBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T09:34:13.967264Z","bundle_sha256":"d41701012b322b1ceca4b0be657411663625690e658c232bd203531a90d8d622"}}