{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:AGLGU7WHEXMWOC6J7OH6P56O2R","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":"a55245b73585905cf994ebb1a6ffb34b5fc0dd3141749e3c46e788bc5864a5d5","cross_cats_sorted":["cs.GR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-08-08T17:16:02Z","title_canon_sha256":"8b032243175502c4a47944fe669a17fd504b0943bc10f48eeb479471e80bae38"},"schema_version":"1.0","source":{"id":"2208.04278","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.04278","created_at":"2026-07-05T05:27:34Z"},{"alias_kind":"arxiv_version","alias_value":"2208.04278v2","created_at":"2026-07-05T05:27:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.04278","created_at":"2026-07-05T05:27:34Z"},{"alias_kind":"pith_short_12","alias_value":"AGLGU7WHEXMW","created_at":"2026-07-05T05:27:34Z"},{"alias_kind":"pith_short_16","alias_value":"AGLGU7WHEXMWOC6J","created_at":"2026-07-05T05:27:34Z"},{"alias_kind":"pith_short_8","alias_value":"AGLGU7WH","created_at":"2026-07-05T05:27:34Z"}],"graph_snapshots":[{"event_id":"sha256:249af10aa5ce381bca9a05b73a580e3a30cde60230c94118c17ddb630db55969","target":"graph","created_at":"2026-07-05T05:27:34Z","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/2208.04278/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"3D deep learning is a growing field of interest due to the vast amount of information stored in 3D formats. Triangular meshes are an efficient representation for irregular, non-uniform 3D objects. However, meshes are often challenging to annotate due to their high geometrical complexity. Specifically, creating segmentation masks for meshes is tedious and time-consuming. Therefore, it is desirable to train segmentation networks with limited-labeled data. Self-supervised learning (SSL), a form of unsupervised representation learning, is a growing alternative to fully-supervised learning which ca","authors_text":"Ayaan Haque, Hankyu Moon, Heng Hao, Jae Oh Woo, Patrick Bangert, Sima Didari","cross_cats":["cs.GR","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-08-08T17:16:02Z","title":"Self-Supervised Contrastive Representation Learning for 3D Mesh Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.04278","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":"sha256:751bb65c0a9c7bedeaa5499b6aee79ec6401d53c2e7455f399a2a75696ee3d86","target":"record","created_at":"2026-07-05T05:27:34Z","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":"a55245b73585905cf994ebb1a6ffb34b5fc0dd3141749e3c46e788bc5864a5d5","cross_cats_sorted":["cs.GR","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-08-08T17:16:02Z","title_canon_sha256":"8b032243175502c4a47944fe669a17fd504b0943bc10f48eeb479471e80bae38"},"schema_version":"1.0","source":{"id":"2208.04278","kind":"arxiv","version":2}},"canonical_sha256":"01966a7ec725d9670bc9fb8fe7f7ced456cb86985d827b5527180d01cbf2e246","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"01966a7ec725d9670bc9fb8fe7f7ced456cb86985d827b5527180d01cbf2e246","first_computed_at":"2026-07-05T05:27:34.698823Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:27:34.698823Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bcuGaH2HaTNczdOqSxnhty5C1fv5HNTjicSYGJLU+pRXtQm3tWOQZIZJOALz6JpHzDDJ0Ut0rarKsD/ZoWARAg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:27:34.699394Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.04278","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:751bb65c0a9c7bedeaa5499b6aee79ec6401d53c2e7455f399a2a75696ee3d86","sha256:249af10aa5ce381bca9a05b73a580e3a30cde60230c94118c17ddb630db55969"],"state_sha256":"890116879dab896c632bae72a50963eb357fa7321cbf880da9394d32a08f59e6"}