{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:WAPQUWX5NQV6VBPICQDM3WMUVX","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":"25eb5f202b239ae7c439702e53181c637fee9e76ba183ceeb25f10c223361364","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-13T03:45:58Z","title_canon_sha256":"f7781aa1b4803d47325fa27302c0df225d41884f9bff20c77ef40989d4957b8a"},"schema_version":"1.0","source":{"id":"2203.06558","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.06558","created_at":"2026-07-05T04:15:01Z"},{"alias_kind":"arxiv_version","alias_value":"2203.06558v4","created_at":"2026-07-05T04:15:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.06558","created_at":"2026-07-05T04:15:01Z"},{"alias_kind":"pith_short_12","alias_value":"WAPQUWX5NQV6","created_at":"2026-07-05T04:15:01Z"},{"alias_kind":"pith_short_16","alias_value":"WAPQUWX5NQV6VBPI","created_at":"2026-07-05T04:15:01Z"},{"alias_kind":"pith_short_8","alias_value":"WAPQUWX5","created_at":"2026-07-05T04:15:01Z"}],"graph_snapshots":[{"event_id":"sha256:432bd183eac17754f4c02e6e9971e609e5b8ac48c239afb7173ec5deb0b39ca7","target":"graph","created_at":"2026-07-05T04:15:01Z","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/2203.06558/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Training a generalizable 3D part segmentation network is quite challenging but of great importance in real-world applications. To tackle this problem, some works design task-specific solutions by translating human understanding of the task to machine's learning process, which faces the risk of missing the optimal strategy since machines do not necessarily understand in the exact human way. Others try to use conventional task-agnostic approaches designed for domain generalization problems with no task prior knowledge considered. To solve the above issues, we propose AutoGPart, a generic method ","authors_text":"Anyi Rao, Chuang Gan, Li Yi, Xiaomeng Xu, Xueyi Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-13T03:45:58Z","title":"AutoGPart: Intermediate Supervision Search for Generalizable 3D Part Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.06558","kind":"arxiv","version":4},"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:a6ec6786b35063c66524caf843ec9f86dc160905e9bf7bf3c9e2baf027565ad5","target":"record","created_at":"2026-07-05T04:15:01Z","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":"25eb5f202b239ae7c439702e53181c637fee9e76ba183ceeb25f10c223361364","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-13T03:45:58Z","title_canon_sha256":"f7781aa1b4803d47325fa27302c0df225d41884f9bff20c77ef40989d4957b8a"},"schema_version":"1.0","source":{"id":"2203.06558","kind":"arxiv","version":4}},"canonical_sha256":"b01f0a5afd6c2bea85e81406cdd994adc040b351b158dc2380eca799327a4701","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b01f0a5afd6c2bea85e81406cdd994adc040b351b158dc2380eca799327a4701","first_computed_at":"2026-07-05T04:15:01.055621Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:15:01.055621Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nW6rLVTy9rOvCX/MsZc3zaidnRqiD78MDFk9WN+MBilSR3yeYa1rsZBNknL7NrvtS9ES9+YpGCqcvc0LPHr6CA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:15:01.056118Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.06558","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a6ec6786b35063c66524caf843ec9f86dc160905e9bf7bf3c9e2baf027565ad5","sha256:432bd183eac17754f4c02e6e9971e609e5b8ac48c239afb7173ec5deb0b39ca7"],"state_sha256":"b069a474fdeda755dc309cd45fe11d4d4e21b68354dec4670c43a5c81c667dcd"}