{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ON6KY5A265H6SWYHSJUGKRHNXK","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":"179e60d74544634589ac470aea9793d12e868433c96d13f22325e3b1f30c805d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-05-28T17:45:05Z","title_canon_sha256":"6113cdd179b1ea45d87316a0e28e08c35b3eedff9c8a1dc3c5265b3233a7e3d5"},"schema_version":"1.0","source":{"id":"2505.22626","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.22626","created_at":"2026-07-05T12:07:07Z"},{"alias_kind":"arxiv_version","alias_value":"2505.22626v2","created_at":"2026-07-05T12:07:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.22626","created_at":"2026-07-05T12:07:07Z"},{"alias_kind":"pith_short_12","alias_value":"ON6KY5A265H6","created_at":"2026-07-05T12:07:07Z"},{"alias_kind":"pith_short_16","alias_value":"ON6KY5A265H6SWYH","created_at":"2026-07-05T12:07:07Z"},{"alias_kind":"pith_short_8","alias_value":"ON6KY5A2","created_at":"2026-07-05T12:07:07Z"}],"graph_snapshots":[{"event_id":"sha256:0bacb58d8aa548c6f394a9b1635d83068497545af69cb16a5ba294d8d1f121f7","target":"graph","created_at":"2026-07-05T12:07:07Z","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/2505.22626/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Imitation learning advances robot capabilities by enabling the acquisition of diverse behaviors from human demonstrations. However, large-scale datasets used for policy training often introduce substantial variability in quality, which can negatively impact performance. As a result, automatically curating datasets by filtering low-quality samples to improve quality becomes essential. Existing robotic curation approaches rely on costly manual annotations and perform curation at a coarse granularity, such as the dataset or trajectory level, failing to account for the quality of individual state-","authors_text":"Huihan Liu, Linxi Fan, Michael Wan, Rutav Shah, Yuke Zhu, Yuqi Xie, Yu Zhang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-05-28T17:45:05Z","title":"SCIZOR: A Self-Supervised Approach to Data Curation for Large-Scale Imitation Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.22626","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:fc40a0bafae689792350d3f5ae5110c5cc31c064b82c83e51ff6c2039dade91c","target":"record","created_at":"2026-07-05T12:07:07Z","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":"179e60d74544634589ac470aea9793d12e868433c96d13f22325e3b1f30c805d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-05-28T17:45:05Z","title_canon_sha256":"6113cdd179b1ea45d87316a0e28e08c35b3eedff9c8a1dc3c5265b3233a7e3d5"},"schema_version":"1.0","source":{"id":"2505.22626","kind":"arxiv","version":2}},"canonical_sha256":"737cac741af74fe95b0792686544edba8834b380686a96f203c270eec4c362a3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"737cac741af74fe95b0792686544edba8834b380686a96f203c270eec4c362a3","first_computed_at":"2026-07-05T12:07:07.981874Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:07:07.981874Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SP0zvzaAdtL7BqyhMeLDaPXejgI3I3zYxVJ2po7zoYsEqcQ8zVo5IUTmqwgG+z1lFOYaq/02zTfGkAyJD88GBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:07:07.982384Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.22626","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fc40a0bafae689792350d3f5ae5110c5cc31c064b82c83e51ff6c2039dade91c","sha256:0bacb58d8aa548c6f394a9b1635d83068497545af69cb16a5ba294d8d1f121f7"],"state_sha256":"5f083fc0f1198f539003bd28896e0de7053ce7c2d24bd7ce375b5bbbda58561e"}