{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:QCJZYRJ5AXGFMWAIE3H5IFEVV7","short_pith_number":"pith:QCJZYRJ5","canonical_record":{"source":{"id":"2211.00194","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-10-31T23:37:29Z","cross_cats_sorted":[],"title_canon_sha256":"b070a2340b180d3fda6200ca5ad477e2edb00abe0c6e1113ec66269204af6baf","abstract_canon_sha256":"564ef2507713cd4afcea0529498a2f6fa9e49f2f5038ea026f277877af4fbdc4"},"schema_version":"1.0"},"canonical_sha256":"80939c453d05cc56580826cfd41495afc9e7faf7c1b33832203237f3ea3427c1","source":{"kind":"arxiv","id":"2211.00194","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.00194","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"arxiv_version","alias_value":"2211.00194v1","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.00194","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"pith_short_12","alias_value":"QCJZYRJ5AXGF","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"pith_short_16","alias_value":"QCJZYRJ5AXGFMWAI","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"pith_short_8","alias_value":"QCJZYRJ5","created_at":"2026-07-05T05:12:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:QCJZYRJ5AXGFMWAIE3H5IFEVV7","target":"record","payload":{"canonical_record":{"source":{"id":"2211.00194","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-10-31T23:37:29Z","cross_cats_sorted":[],"title_canon_sha256":"b070a2340b180d3fda6200ca5ad477e2edb00abe0c6e1113ec66269204af6baf","abstract_canon_sha256":"564ef2507713cd4afcea0529498a2f6fa9e49f2f5038ea026f277877af4fbdc4"},"schema_version":"1.0"},"canonical_sha256":"80939c453d05cc56580826cfd41495afc9e7faf7c1b33832203237f3ea3427c1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:12:19.761411Z","signature_b64":"eE22iMpbIwc0aARYY+y62+NcmSDPp7f7tN5a0Rd5H7uqmetiXqU4Oq9jxai+y12iRfliIAtBVzw4SZC76QpbDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"80939c453d05cc56580826cfd41495afc9e7faf7c1b33832203237f3ea3427c1","last_reissued_at":"2026-07-05T05:12:19.760939Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:12:19.760939Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.00194","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":"2026-07-05T05:12:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s2DeZp5FV5w9pbB8rrbQSylay9I/Jxoe28D2PvmuPvA7onM9T8K2uxRHBFzbBYkeCSN55S/SL4kSRLqk4bUxBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:12:43.278299Z"},"content_sha256":"6960518f66c4999023801bf49169e5a06ea3f6554cc59ec090302210ea9c5ac5","schema_version":"1.0","event_id":"sha256:6960518f66c4999023801bf49169e5a06ea3f6554cc59ec090302210ea9c5ac5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:QCJZYRJ5AXGFMWAIE3H5IFEVV7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SEIL: Simulation-augmented Equivariant Imitation Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"David Klee, Dian Wang, Guanang Su, Mingxi Jia, Robert Platt, Robin Walters, Xupeng Zhu","submitted_at":"2022-10-31T23:37:29Z","abstract_excerpt":"In robotic manipulation, acquiring samples is extremely expensive because it often requires interacting with the real world. Traditional image-level data augmentation has shown the potential to improve sample efficiency in various machine learning tasks. However, image-level data augmentation is insufficient for an imitation learning agent to learn good manipulation policies in a reasonable amount of demonstrations. We propose Simulation-augmented Equivariant Imitation Learning (SEIL), a method that combines a novel data augmentation strategy of supplementing expert trajectories with simulated"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.00194","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/2211.00194/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":"2026-07-05T05:12:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QnYWGx7yroMxe/niwNq6jRemXudCGDZB1TYqSVu6JADNOCi9D1gsi7gd8b/fBmMNky4y659/IZX6X+ZxMmMNCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:12:43.278683Z"},"content_sha256":"4d5b355209296a016813aa33b0d2e710efe3afc54d6f205c006c8492f525a2ac","schema_version":"1.0","event_id":"sha256:4d5b355209296a016813aa33b0d2e710efe3afc54d6f205c006c8492f525a2ac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QCJZYRJ5AXGFMWAIE3H5IFEVV7/bundle.json","state_url":"https://pith.science/pith/QCJZYRJ5AXGFMWAIE3H5IFEVV7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QCJZYRJ5AXGFMWAIE3H5IFEVV7/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":"2026-07-06T18:12:43Z","links":{"resolver":"https://pith.science/pith/QCJZYRJ5AXGFMWAIE3H5IFEVV7","bundle":"https://pith.science/pith/QCJZYRJ5AXGFMWAIE3H5IFEVV7/bundle.json","state":"https://pith.science/pith/QCJZYRJ5AXGFMWAIE3H5IFEVV7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QCJZYRJ5AXGFMWAIE3H5IFEVV7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:QCJZYRJ5AXGFMWAIE3H5IFEVV7","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":"564ef2507713cd4afcea0529498a2f6fa9e49f2f5038ea026f277877af4fbdc4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-10-31T23:37:29Z","title_canon_sha256":"b070a2340b180d3fda6200ca5ad477e2edb00abe0c6e1113ec66269204af6baf"},"schema_version":"1.0","source":{"id":"2211.00194","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.00194","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"arxiv_version","alias_value":"2211.00194v1","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.00194","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"pith_short_12","alias_value":"QCJZYRJ5AXGF","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"pith_short_16","alias_value":"QCJZYRJ5AXGFMWAI","created_at":"2026-07-05T05:12:19Z"},{"alias_kind":"pith_short_8","alias_value":"QCJZYRJ5","created_at":"2026-07-05T05:12:19Z"}],"graph_snapshots":[{"event_id":"sha256:4d5b355209296a016813aa33b0d2e710efe3afc54d6f205c006c8492f525a2ac","target":"graph","created_at":"2026-07-05T05:12:19Z","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/2211.00194/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In robotic manipulation, acquiring samples is extremely expensive because it often requires interacting with the real world. Traditional image-level data augmentation has shown the potential to improve sample efficiency in various machine learning tasks. However, image-level data augmentation is insufficient for an imitation learning agent to learn good manipulation policies in a reasonable amount of demonstrations. We propose Simulation-augmented Equivariant Imitation Learning (SEIL), a method that combines a novel data augmentation strategy of supplementing expert trajectories with simulated","authors_text":"David Klee, Dian Wang, Guanang Su, Mingxi Jia, Robert Platt, Robin Walters, Xupeng Zhu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-10-31T23:37:29Z","title":"SEIL: Simulation-augmented Equivariant Imitation Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.00194","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":"sha256:6960518f66c4999023801bf49169e5a06ea3f6554cc59ec090302210ea9c5ac5","target":"record","created_at":"2026-07-05T05:12:19Z","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":"564ef2507713cd4afcea0529498a2f6fa9e49f2f5038ea026f277877af4fbdc4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-10-31T23:37:29Z","title_canon_sha256":"b070a2340b180d3fda6200ca5ad477e2edb00abe0c6e1113ec66269204af6baf"},"schema_version":"1.0","source":{"id":"2211.00194","kind":"arxiv","version":1}},"canonical_sha256":"80939c453d05cc56580826cfd41495afc9e7faf7c1b33832203237f3ea3427c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"80939c453d05cc56580826cfd41495afc9e7faf7c1b33832203237f3ea3427c1","first_computed_at":"2026-07-05T05:12:19.760939Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:12:19.760939Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eE22iMpbIwc0aARYY+y62+NcmSDPp7f7tN5a0Rd5H7uqmetiXqU4Oq9jxai+y12iRfliIAtBVzw4SZC76QpbDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:12:19.761411Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.00194","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6960518f66c4999023801bf49169e5a06ea3f6554cc59ec090302210ea9c5ac5","sha256:4d5b355209296a016813aa33b0d2e710efe3afc54d6f205c006c8492f525a2ac"],"state_sha256":"c55f53c7e027ee14f9d9d3f539094f64457e02570a662e330e0850aa082aaa93"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aNKYCRCoucNXOzgeY6uqeDV1y4sl26z3iWqnmoGgwL2v8dg6aMT7TjiGy2w9Nyt4ZBk+p1URO43n9/fnptx6Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:12:43.280479Z","bundle_sha256":"a8779894c004969c4a7dd4783d83d531255a82c0c6f3fb090511427ef6e359ea"}}