{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:23R6OZFSJ6KTVYVAYD4GX5WQGC","short_pith_number":"pith:23R6OZFS","canonical_record":{"source":{"id":"2108.12178","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-27T08:47:01Z","cross_cats_sorted":[],"title_canon_sha256":"34d8c65352b02616ae6ab9ab9895c2edb62def67e2c06acc6a4263a650abde11","abstract_canon_sha256":"8ab6e6822c691bc84de700c0294f6bc553079ce20b201af417dacb03f7f68be1"},"schema_version":"1.0"},"canonical_sha256":"d6e3e764b24f953ae2a0c0f86bf6d030a2f8d19d6dae3ccb660287876e52faf8","source":{"kind":"arxiv","id":"2108.12178","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.12178","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"arxiv_version","alias_value":"2108.12178v1","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.12178","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"pith_short_12","alias_value":"23R6OZFSJ6KT","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"pith_short_16","alias_value":"23R6OZFSJ6KTVYVA","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"pith_short_8","alias_value":"23R6OZFS","created_at":"2026-07-05T03:09:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:23R6OZFSJ6KTVYVAYD4GX5WQGC","target":"record","payload":{"canonical_record":{"source":{"id":"2108.12178","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-27T08:47:01Z","cross_cats_sorted":[],"title_canon_sha256":"34d8c65352b02616ae6ab9ab9895c2edb62def67e2c06acc6a4263a650abde11","abstract_canon_sha256":"8ab6e6822c691bc84de700c0294f6bc553079ce20b201af417dacb03f7f68be1"},"schema_version":"1.0"},"canonical_sha256":"d6e3e764b24f953ae2a0c0f86bf6d030a2f8d19d6dae3ccb660287876e52faf8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:09:22.755999Z","signature_b64":"H5iuxNqttK2o32r5jMH3VIDzqKGjeL1gx3a2RX8GMc8h0pmxGeFspN4jK6VHtjguGmD8UWTyDOc+aJMBR05/Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6e3e764b24f953ae2a0c0f86bf6d030a2f8d19d6dae3ccb660287876e52faf8","last_reissued_at":"2026-07-05T03:09:22.755561Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:09:22.755561Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2108.12178","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:09:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I9FEuNwiNRhMA0j6dnbRMTZ23NM0BXql4w5mLjcej6vPHpVAMXe5FaoqW0iZjg2Xmre68jJt8EDuer2ZvY8tDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T00:14:49.521423Z"},"content_sha256":"4a911bae59661e628dffc076b57a960a3b71efac60f9a0d4ce192e0e2e4c66c0","schema_version":"1.0","event_id":"sha256:4a911bae59661e628dffc076b57a960a3b71efac60f9a0d4ce192e0e2e4c66c0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:23R6OZFSJ6KTVYVAYD4GX5WQGC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dit-Yan Yeung, Hang Xu, Kai Chen, Lanqing Hong, Zhenguo Li","submitted_at":"2021-08-27T08:47:01Z","abstract_excerpt":"Autonomous driving has attracted much attention over the years but turns out to be harder than expected, probably due to the difficulty of labeled data collection for model training. Self-supervised learning (SSL), which leverages unlabeled data only for representation learning, might be a promising way to improve model performance. Existing SSL methods, however, usually rely on the single-centric-object guarantee, which may not be applicable for multi-instance datasets such as street scenes. To alleviate this limitation, we raise two issues to solve: (1) how to define positive samples for cro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.12178","kind":"arxiv","version":1},"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/2108.12178/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":"2026-07-05T03:09:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t+I8wGkkppEE3GDvRBR5ZI+nMYTCQpeal1y8LMowjX0RmlTlvQIY3g8vbj44wpYHcNQuoMDp8u1km8ZINmhEBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T00:14:49.521807Z"},"content_sha256":"4eb9b0bf5c2a8a1062a460d1edabd87aedfca7231fb0212c0b228c00f1b4a493","schema_version":"1.0","event_id":"sha256:4eb9b0bf5c2a8a1062a460d1edabd87aedfca7231fb0212c0b228c00f1b4a493"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/23R6OZFSJ6KTVYVAYD4GX5WQGC/bundle.json","state_url":"https://pith.science/pith/23R6OZFSJ6KTVYVAYD4GX5WQGC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/23R6OZFSJ6KTVYVAYD4GX5WQGC/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":"2026-08-07T00:14:49Z","links":{"resolver":"https://pith.science/pith/23R6OZFSJ6KTVYVAYD4GX5WQGC","bundle":"https://pith.science/pith/23R6OZFSJ6KTVYVAYD4GX5WQGC/bundle.json","state":"https://pith.science/pith/23R6OZFSJ6KTVYVAYD4GX5WQGC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/23R6OZFSJ6KTVYVAYD4GX5WQGC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:23R6OZFSJ6KTVYVAYD4GX5WQGC","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":"8ab6e6822c691bc84de700c0294f6bc553079ce20b201af417dacb03f7f68be1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-27T08:47:01Z","title_canon_sha256":"34d8c65352b02616ae6ab9ab9895c2edb62def67e2c06acc6a4263a650abde11"},"schema_version":"1.0","source":{"id":"2108.12178","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.12178","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"arxiv_version","alias_value":"2108.12178v1","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.12178","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"pith_short_12","alias_value":"23R6OZFSJ6KT","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"pith_short_16","alias_value":"23R6OZFSJ6KTVYVA","created_at":"2026-07-05T03:09:22Z"},{"alias_kind":"pith_short_8","alias_value":"23R6OZFS","created_at":"2026-07-05T03:09:22Z"}],"graph_snapshots":[{"event_id":"sha256:4eb9b0bf5c2a8a1062a460d1edabd87aedfca7231fb0212c0b228c00f1b4a493","target":"graph","created_at":"2026-07-05T03:09:22Z","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/2108.12178/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Autonomous driving has attracted much attention over the years but turns out to be harder than expected, probably due to the difficulty of labeled data collection for model training. Self-supervised learning (SSL), which leverages unlabeled data only for representation learning, might be a promising way to improve model performance. Existing SSL methods, however, usually rely on the single-centric-object guarantee, which may not be applicable for multi-instance datasets such as street scenes. To alleviate this limitation, we raise two issues to solve: (1) how to define positive samples for cro","authors_text":"Dit-Yan Yeung, Hang Xu, Kai Chen, Lanqing Hong, Zhenguo Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-27T08:47:01Z","title":"MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.12178","kind":"arxiv","version":1},"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":"sha256:4a911bae59661e628dffc076b57a960a3b71efac60f9a0d4ce192e0e2e4c66c0","target":"record","created_at":"2026-07-05T03:09:22Z","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":"8ab6e6822c691bc84de700c0294f6bc553079ce20b201af417dacb03f7f68be1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-08-27T08:47:01Z","title_canon_sha256":"34d8c65352b02616ae6ab9ab9895c2edb62def67e2c06acc6a4263a650abde11"},"schema_version":"1.0","source":{"id":"2108.12178","kind":"arxiv","version":1}},"canonical_sha256":"d6e3e764b24f953ae2a0c0f86bf6d030a2f8d19d6dae3ccb660287876e52faf8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d6e3e764b24f953ae2a0c0f86bf6d030a2f8d19d6dae3ccb660287876e52faf8","first_computed_at":"2026-07-05T03:09:22.755561Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:09:22.755561Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"H5iuxNqttK2o32r5jMH3VIDzqKGjeL1gx3a2RX8GMc8h0pmxGeFspN4jK6VHtjguGmD8UWTyDOc+aJMBR05/Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:09:22.755999Z","signed_message":"canonical_sha256_bytes"},"source_id":"2108.12178","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a911bae59661e628dffc076b57a960a3b71efac60f9a0d4ce192e0e2e4c66c0","sha256:4eb9b0bf5c2a8a1062a460d1edabd87aedfca7231fb0212c0b228c00f1b4a493"],"state_sha256":"225c1f2afe37c411cbe4cdf990e991bf695a4c19e412cb9a655f6abfbdb0d1f3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3oSGbANNd2SXjkzNL/mw+tM6wwwlofDkG5NV+PjfFsNpRGea5PmodNqKUeg4nWC6TBM6Cx1g77ppIytOMz4lBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T00:14:49.524189Z","bundle_sha256":"f21a3ffe7407687ca4db4a5b97cb12949e8e5c05ce55c1a7a7d5df45466a2261"}}