{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:USLV6KGLZ4VYUQP5ECLJMO6O6T","short_pith_number":"pith:USLV6KGL","canonical_record":{"source":{"id":"2306.05246","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-08T14:44:57Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"d60367128bdbd351a7dfaf06480082422c05fcf06038cbeb0de37537018046dc","abstract_canon_sha256":"e1620db7a1e6c42ad9f004727f1c1df511ea8a9fe78dc0e93c4a13e052a803a4"},"schema_version":"1.0"},"canonical_sha256":"a4975f28cbcf2b8a41fd2096963bcef4c2de13e6af9a40393035d6376fcb46a6","source":{"kind":"arxiv","id":"2306.05246","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.05246","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"arxiv_version","alias_value":"2306.05246v3","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.05246","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"pith_short_12","alias_value":"USLV6KGLZ4VY","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"pith_short_16","alias_value":"USLV6KGLZ4VYUQP5","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"pith_short_8","alias_value":"USLV6KGL","created_at":"2026-07-05T07:28:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:USLV6KGLZ4VYUQP5ECLJMO6O6T","target":"record","payload":{"canonical_record":{"source":{"id":"2306.05246","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-08T14:44:57Z","cross_cats_sorted":["cs.GR"],"title_canon_sha256":"d60367128bdbd351a7dfaf06480082422c05fcf06038cbeb0de37537018046dc","abstract_canon_sha256":"e1620db7a1e6c42ad9f004727f1c1df511ea8a9fe78dc0e93c4a13e052a803a4"},"schema_version":"1.0"},"canonical_sha256":"a4975f28cbcf2b8a41fd2096963bcef4c2de13e6af9a40393035d6376fcb46a6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:28:28.489820Z","signature_b64":"PEYx44jllk4FbGf7dD/U7WK0tNvXI9VXqFIwc7HrQnu9ZTc0rVuhd48/jLZkZGMSLh0uJkZRwpnTACpZqCdvCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a4975f28cbcf2b8a41fd2096963bcef4c2de13e6af9a40393035d6376fcb46a6","last_reissued_at":"2026-07-05T07:28:28.489395Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:28:28.489395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.05246","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:28:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fQR+o3Z9f2sHF65CpbdZV9zGaQnx5QQ/9P3Iq+Rbw1Jrz1ds0FybmcT8JQZ32VEJ2+KbNM+Z49N2jJU7/zFnDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T23:02:01.405431Z"},"content_sha256":"97440d9e043b7c458f3295fdb6d1bac7ae1a822527a4508062a5229c4bcb4b64","schema_version":"1.0","event_id":"sha256:97440d9e043b7c458f3295fdb6d1bac7ae1a822527a4508062a5229c4bcb4b64"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:USLV6KGLZ4VYUQP5ECLJMO6O6T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Task-driven Network for Mesh Classification and Semantic Part Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.GR"],"primary_cat":"cs.CV","authors_text":"Changhe Tu, Qiujie Dong, Rui Xu, Shiqing Xin, Shuangmin Chen, Wenping Wang, Xiaoran Gong, Zixiong Wang","submitted_at":"2023-06-08T14:44:57Z","abstract_excerpt":"With the rapid development of geometric deep learning techniques, many mesh-based convolutional operators have been proposed to bridge irregular mesh structures and popular backbone networks. In this paper, we show that while convolutions are helpful, a simple architecture based exclusively on multi-layer perceptrons (MLPs) is competent enough to deal with mesh classification and semantic segmentation. Our new network architecture, named Mesh-MLP, takes mesh vertices equipped with the heat kernel signature (HKS) and dihedral angles as the input, replaces the convolution module of a ResNet with"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.05246","kind":"arxiv","version":3},"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/2306.05246/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":"2026-07-05T07:28:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7DiTAmgbeQmwaJ2nlfRgYIZd6HhQcL46wyqcLvscV+tKOvfgjU5zMii8qs/QCWwfeqj2FdLAPuRgDAsZta1KAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T23:02:01.406010Z"},"content_sha256":"8896b4af658890a682309ee0bd00ae817e652dbd2949b953b3b0d7b295782811","schema_version":"1.0","event_id":"sha256:8896b4af658890a682309ee0bd00ae817e652dbd2949b953b3b0d7b295782811"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/USLV6KGLZ4VYUQP5ECLJMO6O6T/bundle.json","state_url":"https://pith.science/pith/USLV6KGLZ4VYUQP5ECLJMO6O6T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/USLV6KGLZ4VYUQP5ECLJMO6O6T/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":"2026-08-21T23:02:01Z","links":{"resolver":"https://pith.science/pith/USLV6KGLZ4VYUQP5ECLJMO6O6T","bundle":"https://pith.science/pith/USLV6KGLZ4VYUQP5ECLJMO6O6T/bundle.json","state":"https://pith.science/pith/USLV6KGLZ4VYUQP5ECLJMO6O6T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/USLV6KGLZ4VYUQP5ECLJMO6O6T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:USLV6KGLZ4VYUQP5ECLJMO6O6T","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":"e1620db7a1e6c42ad9f004727f1c1df511ea8a9fe78dc0e93c4a13e052a803a4","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-08T14:44:57Z","title_canon_sha256":"d60367128bdbd351a7dfaf06480082422c05fcf06038cbeb0de37537018046dc"},"schema_version":"1.0","source":{"id":"2306.05246","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.05246","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"arxiv_version","alias_value":"2306.05246v3","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.05246","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"pith_short_12","alias_value":"USLV6KGLZ4VY","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"pith_short_16","alias_value":"USLV6KGLZ4VYUQP5","created_at":"2026-07-05T07:28:28Z"},{"alias_kind":"pith_short_8","alias_value":"USLV6KGL","created_at":"2026-07-05T07:28:28Z"}],"graph_snapshots":[{"event_id":"sha256:8896b4af658890a682309ee0bd00ae817e652dbd2949b953b3b0d7b295782811","target":"graph","created_at":"2026-07-05T07:28:28Z","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/2306.05246/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the rapid development of geometric deep learning techniques, many mesh-based convolutional operators have been proposed to bridge irregular mesh structures and popular backbone networks. In this paper, we show that while convolutions are helpful, a simple architecture based exclusively on multi-layer perceptrons (MLPs) is competent enough to deal with mesh classification and semantic segmentation. Our new network architecture, named Mesh-MLP, takes mesh vertices equipped with the heat kernel signature (HKS) and dihedral angles as the input, replaces the convolution module of a ResNet with","authors_text":"Changhe Tu, Qiujie Dong, Rui Xu, Shiqing Xin, Shuangmin Chen, Wenping Wang, Xiaoran Gong, Zixiong Wang","cross_cats":["cs.GR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-08T14:44:57Z","title":"A Task-driven Network for Mesh Classification and Semantic Part Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.05246","kind":"arxiv","version":3},"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":"sha256:97440d9e043b7c458f3295fdb6d1bac7ae1a822527a4508062a5229c4bcb4b64","target":"record","created_at":"2026-07-05T07:28:28Z","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":"e1620db7a1e6c42ad9f004727f1c1df511ea8a9fe78dc0e93c4a13e052a803a4","cross_cats_sorted":["cs.GR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-08T14:44:57Z","title_canon_sha256":"d60367128bdbd351a7dfaf06480082422c05fcf06038cbeb0de37537018046dc"},"schema_version":"1.0","source":{"id":"2306.05246","kind":"arxiv","version":3}},"canonical_sha256":"a4975f28cbcf2b8a41fd2096963bcef4c2de13e6af9a40393035d6376fcb46a6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a4975f28cbcf2b8a41fd2096963bcef4c2de13e6af9a40393035d6376fcb46a6","first_computed_at":"2026-07-05T07:28:28.489395Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:28:28.489395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PEYx44jllk4FbGf7dD/U7WK0tNvXI9VXqFIwc7HrQnu9ZTc0rVuhd48/jLZkZGMSLh0uJkZRwpnTACpZqCdvCw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:28:28.489820Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.05246","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:97440d9e043b7c458f3295fdb6d1bac7ae1a822527a4508062a5229c4bcb4b64","sha256:8896b4af658890a682309ee0bd00ae817e652dbd2949b953b3b0d7b295782811"],"state_sha256":"cb500df66ca9072f5401cdc7e5376295be216dc39e7ccf1229ca7c969d4969a4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dZqV986RYF5BdmEPCx/RP+Psrged5+SfEkRAfVdz69zVLeNT+Pmbv6WjslVy96IcNOqwfoCB4ehmvVsCtlPPBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T23:02:01.411859Z","bundle_sha256":"ae6bfe00757e5d5514e408a996d1969035881f77f8af1f70b8cfc97f94274418"}}