{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:VWWHPB3A7LDFLZSEEFRFGEGNKQ","short_pith_number":"pith:VWWHPB3A","canonical_record":{"source":{"id":"1905.11979","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T17:56:19Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"e591589acc60cda46ec6dfa4b46f6eef52ee3a144cfb70e47baab13b2391c907","abstract_canon_sha256":"4025d313cdd913f880aa500bc343722abc32fe9883832420b3fdf68321cda796"},"schema_version":"1.0"},"canonical_sha256":"adac778760fac655e64421625310cd543fe4e309fa54574d5dc0b75f4cc8ad54","source":{"kind":"arxiv","id":"1905.11979","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.11979","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"arxiv_version","alias_value":"1905.11979v2","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.11979","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"pith_short_12","alias_value":"VWWHPB3A7LDF","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"pith_short_16","alias_value":"VWWHPB3A7LDFLZSE","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"pith_short_8","alias_value":"VWWHPB3A","created_at":"2026-07-05T00:16:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:VWWHPB3A7LDFLZSEEFRFGEGNKQ","target":"record","payload":{"canonical_record":{"source":{"id":"1905.11979","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T17:56:19Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"e591589acc60cda46ec6dfa4b46f6eef52ee3a144cfb70e47baab13b2391c907","abstract_canon_sha256":"4025d313cdd913f880aa500bc343722abc32fe9883832420b3fdf68321cda796"},"schema_version":"1.0"},"canonical_sha256":"adac778760fac655e64421625310cd543fe4e309fa54574d5dc0b75f4cc8ad54","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:16:34.729432Z","signature_b64":"cqAHjg9CCe8llBnPyBxYYllT/BafvcRMW4YRSZ4FLAnnYD2JK4b9AhkV2jbDegm8brMiqp/FfhL6N9aNsgxAAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"adac778760fac655e64421625310cd543fe4e309fa54574d5dc0b75f4cc8ad54","last_reissued_at":"2026-07-05T00:16:34.728999Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:16:34.728999Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1905.11979","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":"2026-07-05T00:16:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/AYzjSPWp06fqQ8T6DztELK0LM0CSaRepOI73Mh3A9iyDaew0n/30NnP0U2ohOAzOVUM5rHnOgqpoGynWlOYDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:50:55.803936Z"},"content_sha256":"4a1095301739650f44c9c0244cdf8c1a7bdd08ad11b6f5c7f0c42b4031fba3c2","schema_version":"1.0","event_id":"sha256:4a1095301739650f44c9c0244cdf8c1a7bdd08ad11b6f5c7f0c42b4031fba3c2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:VWWHPB3A7LDFLZSEEFRFGEGNKQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Causal Confusion in Imitation Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Dinesh Jayaraman, Pim de Haan, Sergey Levine","submitted_at":"2019-05-28T17:56:19Z","abstract_excerpt":"Behavioral cloning reduces policy learning to supervised learning by training a discriminative model to predict expert actions given observations. Such discriminative models are non-causal: the training procedure is unaware of the causal structure of the interaction between the expert and the environment. We point out that ignoring causality is particularly damaging because of the distributional shift in imitation learning. In particular, it leads to a counter-intuitive \"causal misidentification\" phenomenon: access to more information can yield worse performance. We investigate how this proble"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.11979","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/1905.11979/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":"2026-07-05T00:16:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G+NGQ3Sezz7PWT9u3BZfg75PIdxy5lV1r6DnON9vLb1uqS2yVkBSd4w4FJy6/R7nmSWRnac9zVHbZlsJ1YP3Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:50:55.804828Z"},"content_sha256":"3504fc5b8f9fe4547fa5d1cf17b816a9639fce6dd46b506567f1540332e5c37d","schema_version":"1.0","event_id":"sha256:3504fc5b8f9fe4547fa5d1cf17b816a9639fce6dd46b506567f1540332e5c37d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VWWHPB3A7LDFLZSEEFRFGEGNKQ/bundle.json","state_url":"https://pith.science/pith/VWWHPB3A7LDFLZSEEFRFGEGNKQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VWWHPB3A7LDFLZSEEFRFGEGNKQ/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":"2026-08-09T10:50:55Z","links":{"resolver":"https://pith.science/pith/VWWHPB3A7LDFLZSEEFRFGEGNKQ","bundle":"https://pith.science/pith/VWWHPB3A7LDFLZSEEFRFGEGNKQ/bundle.json","state":"https://pith.science/pith/VWWHPB3A7LDFLZSEEFRFGEGNKQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VWWHPB3A7LDFLZSEEFRFGEGNKQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:VWWHPB3A7LDFLZSEEFRFGEGNKQ","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":"4025d313cdd913f880aa500bc343722abc32fe9883832420b3fdf68321cda796","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T17:56:19Z","title_canon_sha256":"e591589acc60cda46ec6dfa4b46f6eef52ee3a144cfb70e47baab13b2391c907"},"schema_version":"1.0","source":{"id":"1905.11979","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.11979","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"arxiv_version","alias_value":"1905.11979v2","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.11979","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"pith_short_12","alias_value":"VWWHPB3A7LDF","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"pith_short_16","alias_value":"VWWHPB3A7LDFLZSE","created_at":"2026-07-05T00:16:34Z"},{"alias_kind":"pith_short_8","alias_value":"VWWHPB3A","created_at":"2026-07-05T00:16:34Z"}],"graph_snapshots":[{"event_id":"sha256:3504fc5b8f9fe4547fa5d1cf17b816a9639fce6dd46b506567f1540332e5c37d","target":"graph","created_at":"2026-07-05T00:16:34Z","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/1905.11979/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Behavioral cloning reduces policy learning to supervised learning by training a discriminative model to predict expert actions given observations. Such discriminative models are non-causal: the training procedure is unaware of the causal structure of the interaction between the expert and the environment. We point out that ignoring causality is particularly damaging because of the distributional shift in imitation learning. In particular, it leads to a counter-intuitive \"causal misidentification\" phenomenon: access to more information can yield worse performance. We investigate how this proble","authors_text":"Dinesh Jayaraman, Pim de Haan, Sergey Levine","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T17:56:19Z","title":"Causal Confusion in Imitation Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.11979","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":"sha256:4a1095301739650f44c9c0244cdf8c1a7bdd08ad11b6f5c7f0c42b4031fba3c2","target":"record","created_at":"2026-07-05T00:16:34Z","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":"4025d313cdd913f880aa500bc343722abc32fe9883832420b3fdf68321cda796","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-28T17:56:19Z","title_canon_sha256":"e591589acc60cda46ec6dfa4b46f6eef52ee3a144cfb70e47baab13b2391c907"},"schema_version":"1.0","source":{"id":"1905.11979","kind":"arxiv","version":2}},"canonical_sha256":"adac778760fac655e64421625310cd543fe4e309fa54574d5dc0b75f4cc8ad54","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"adac778760fac655e64421625310cd543fe4e309fa54574d5dc0b75f4cc8ad54","first_computed_at":"2026-07-05T00:16:34.728999Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:16:34.728999Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cqAHjg9CCe8llBnPyBxYYllT/BafvcRMW4YRSZ4FLAnnYD2JK4b9AhkV2jbDegm8brMiqp/FfhL6N9aNsgxAAg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:16:34.729432Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.11979","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a1095301739650f44c9c0244cdf8c1a7bdd08ad11b6f5c7f0c42b4031fba3c2","sha256:3504fc5b8f9fe4547fa5d1cf17b816a9639fce6dd46b506567f1540332e5c37d"],"state_sha256":"c98d871b7aaedaf61ca09c8ec62a085c073c012cfcbb435e2a39244d3a189776"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wNKtIX937SscwHdqLZujlPbyDt7f01dQ32EAJlUyTVzLjFnIcPDwkdXjvSQDAhBaXQKCc/ceIyPs3E+KSPumBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T10:50:55.810776Z","bundle_sha256":"90518a53a790d3bca5ff5f15ead0b144a26019ac3629cb307e8185337d4de3a8"}}