{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:KM6KM3TJHGQ65HPJPMW2RMNLVI","short_pith_number":"pith:KM6KM3TJ","canonical_record":{"source":{"id":"2302.02318","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T06:58:35Z","cross_cats_sorted":[],"title_canon_sha256":"cc36ef78a7df9b351c9d7ed8b9ffe507274a7d94743400773bb1b6160cbc529d","abstract_canon_sha256":"0e631ef5090040781541b538278a1cd0c170e6806542ef2ebaab8ae04ef43b6a"},"schema_version":"1.0"},"canonical_sha256":"533ca66e6939a1ee9de97b2da8b1abaa2145183df456fa01b8688350917dea74","source":{"kind":"arxiv","id":"2302.02318","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.02318","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"arxiv_version","alias_value":"2302.02318v2","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.02318","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_12","alias_value":"KM6KM3TJHGQ6","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_16","alias_value":"KM6KM3TJHGQ65HPJ","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_8","alias_value":"KM6KM3TJ","created_at":"2026-07-05T06:12:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:KM6KM3TJHGQ65HPJPMW2RMNLVI","target":"record","payload":{"canonical_record":{"source":{"id":"2302.02318","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T06:58:35Z","cross_cats_sorted":[],"title_canon_sha256":"cc36ef78a7df9b351c9d7ed8b9ffe507274a7d94743400773bb1b6160cbc529d","abstract_canon_sha256":"0e631ef5090040781541b538278a1cd0c170e6806542ef2ebaab8ae04ef43b6a"},"schema_version":"1.0"},"canonical_sha256":"533ca66e6939a1ee9de97b2da8b1abaa2145183df456fa01b8688350917dea74","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:12:23.771345Z","signature_b64":"Omr5NU4qQuY++H2b6Agdb3Skn40HiP/7Kk80RiZKfi7UIrgVm34IAlEyThx+mrhmz2tSp2DMV4w5WC9lmKAuCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"533ca66e6939a1ee9de97b2da8b1abaa2145183df456fa01b8688350917dea74","last_reissued_at":"2026-07-05T06:12:23.770915Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:12:23.770915Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.02318","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:12:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ITHte7Es7tY8Pu97CQiUgcIHzM4Mhq+ICuNAwwBKiQhcMNpi+RI4KdBBw/LrawJdNd1M+FQ2paJ/MVbxolpDCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T02:45:57.927880Z"},"content_sha256":"52f4a1001694ecce68ce4fc54ed8cfb4ea4267c6d8ecfce19ae62e7af976c9c1","schema_version":"1.0","event_id":"sha256:52f4a1001694ecce68ce4fc54ed8cfb4ea4267c6d8ecfce19ae62e7af976c9c1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:KM6KM3TJHGQ65HPJPMW2RMNLVI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guofan Fan, Kaisheng Ma, Li Yi, Runpei Dong, Xiangyu Zhang, Zekun Qi, Zheng Ge","submitted_at":"2023-02-05T06:58:35Z","abstract_excerpt":"Mainstream 3D representation learning approaches are built upon contrastive or generative modeling pretext tasks, where great improvements in performance on various downstream tasks have been achieved. However, we find these two paradigms have different characteristics: (i) contrastive models are data-hungry that suffer from a representation over-fitting issue; (ii) generative models have a data filling issue that shows inferior data scaling capacity compared to contrastive models. This motivates us to learn 3D representations by sharing the merits of both paradigms, which is non-trivial due t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.02318","kind":"arxiv","version":2},"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/2302.02318/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":"2026-07-05T06:12:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yxIIt8vtUVT8uK65HpaEkpwlqogJfohpRzSthmqfBxb+lHq3CXF9o4uwTcK4+T94tjvu82CUARPSCgaYRpOpDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T02:45:57.928373Z"},"content_sha256":"bfa9d1a71711258c19d7089b1c88e86ce0956fb1a47309097437660327f05f33","schema_version":"1.0","event_id":"sha256:bfa9d1a71711258c19d7089b1c88e86ce0956fb1a47309097437660327f05f33"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KM6KM3TJHGQ65HPJPMW2RMNLVI/bundle.json","state_url":"https://pith.science/pith/KM6KM3TJHGQ65HPJPMW2RMNLVI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KM6KM3TJHGQ65HPJPMW2RMNLVI/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":"2026-08-06T02:45:57Z","links":{"resolver":"https://pith.science/pith/KM6KM3TJHGQ65HPJPMW2RMNLVI","bundle":"https://pith.science/pith/KM6KM3TJHGQ65HPJPMW2RMNLVI/bundle.json","state":"https://pith.science/pith/KM6KM3TJHGQ65HPJPMW2RMNLVI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KM6KM3TJHGQ65HPJPMW2RMNLVI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:KM6KM3TJHGQ65HPJPMW2RMNLVI","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":"0e631ef5090040781541b538278a1cd0c170e6806542ef2ebaab8ae04ef43b6a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T06:58:35Z","title_canon_sha256":"cc36ef78a7df9b351c9d7ed8b9ffe507274a7d94743400773bb1b6160cbc529d"},"schema_version":"1.0","source":{"id":"2302.02318","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.02318","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"arxiv_version","alias_value":"2302.02318v2","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.02318","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_12","alias_value":"KM6KM3TJHGQ6","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_16","alias_value":"KM6KM3TJHGQ65HPJ","created_at":"2026-07-05T06:12:23Z"},{"alias_kind":"pith_short_8","alias_value":"KM6KM3TJ","created_at":"2026-07-05T06:12:23Z"}],"graph_snapshots":[{"event_id":"sha256:bfa9d1a71711258c19d7089b1c88e86ce0956fb1a47309097437660327f05f33","target":"graph","created_at":"2026-07-05T06:12:23Z","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/2302.02318/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mainstream 3D representation learning approaches are built upon contrastive or generative modeling pretext tasks, where great improvements in performance on various downstream tasks have been achieved. However, we find these two paradigms have different characteristics: (i) contrastive models are data-hungry that suffer from a representation over-fitting issue; (ii) generative models have a data filling issue that shows inferior data scaling capacity compared to contrastive models. This motivates us to learn 3D representations by sharing the merits of both paradigms, which is non-trivial due t","authors_text":"Guofan Fan, Kaisheng Ma, Li Yi, Runpei Dong, Xiangyu Zhang, Zekun Qi, Zheng Ge","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T06:58:35Z","title":"Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.02318","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":"sha256:52f4a1001694ecce68ce4fc54ed8cfb4ea4267c6d8ecfce19ae62e7af976c9c1","target":"record","created_at":"2026-07-05T06:12:23Z","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":"0e631ef5090040781541b538278a1cd0c170e6806542ef2ebaab8ae04ef43b6a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T06:58:35Z","title_canon_sha256":"cc36ef78a7df9b351c9d7ed8b9ffe507274a7d94743400773bb1b6160cbc529d"},"schema_version":"1.0","source":{"id":"2302.02318","kind":"arxiv","version":2}},"canonical_sha256":"533ca66e6939a1ee9de97b2da8b1abaa2145183df456fa01b8688350917dea74","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"533ca66e6939a1ee9de97b2da8b1abaa2145183df456fa01b8688350917dea74","first_computed_at":"2026-07-05T06:12:23.770915Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:12:23.770915Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Omr5NU4qQuY++H2b6Agdb3Skn40HiP/7Kk80RiZKfi7UIrgVm34IAlEyThx+mrhmz2tSp2DMV4w5WC9lmKAuCg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:12:23.771345Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.02318","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:52f4a1001694ecce68ce4fc54ed8cfb4ea4267c6d8ecfce19ae62e7af976c9c1","sha256:bfa9d1a71711258c19d7089b1c88e86ce0956fb1a47309097437660327f05f33"],"state_sha256":"4219a23c95681c5c12abce33c476286c848d686c6dbb992e12ff10e60006acc2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hvY3KfCGI3WDS1ITAx5l0pMhSLIJdEB3tznFyUqnCY1t8Th6L/p4W2HqU8UXNvv2iAwA3UZKZaevaqKaR+upDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T02:45:57.931521Z","bundle_sha256":"58e088afdb68427155ce6e72bae4733f1133ccc3326e83b27957132809690041"}}