{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:7QEA7XDJWUPA576W2ZJSVEPVS7","short_pith_number":"pith:7QEA7XDJ","canonical_record":{"source":{"id":"2306.04244","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-07T08:35:27Z","cross_cats_sorted":[],"title_canon_sha256":"051086fd6877407b68a4d8ddb9b78f3b8a674d0ac2558ebff0fca21c095e183d","abstract_canon_sha256":"29cbc2a9413d22341d4d1b93d02b2b3530bb44de9bbda210335013b5f73f7dfe"},"schema_version":"1.0"},"canonical_sha256":"fc080fdc69b51e0effd6d6532a91f597e2b8c28d46417836e5ec751da9d6f848","source":{"kind":"arxiv","id":"2306.04244","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.04244","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"arxiv_version","alias_value":"2306.04244v3","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.04244","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"pith_short_12","alias_value":"7QEA7XDJWUPA","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"pith_short_16","alias_value":"7QEA7XDJWUPA576W","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"pith_short_8","alias_value":"7QEA7XDJ","created_at":"2026-07-05T06:55:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:7QEA7XDJWUPA576W2ZJSVEPVS7","target":"record","payload":{"canonical_record":{"source":{"id":"2306.04244","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-07T08:35:27Z","cross_cats_sorted":[],"title_canon_sha256":"051086fd6877407b68a4d8ddb9b78f3b8a674d0ac2558ebff0fca21c095e183d","abstract_canon_sha256":"29cbc2a9413d22341d4d1b93d02b2b3530bb44de9bbda210335013b5f73f7dfe"},"schema_version":"1.0"},"canonical_sha256":"fc080fdc69b51e0effd6d6532a91f597e2b8c28d46417836e5ec751da9d6f848","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:55:23.863885Z","signature_b64":"UlPLVZ/fyzGzaCttyR2gi0vBxYAo81Nu5NV2Y5+Hif1VDu0Fuk5No3m38Q7xNwu01/e3CWZOJywbDUwDKLuEDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc080fdc69b51e0effd6d6532a91f597e2b8c28d46417836e5ec751da9d6f848","last_reissued_at":"2026-07-05T06:55:23.863424Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:55:23.863424Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.04244","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":"2026-07-05T06:55:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BUN5lFRZd8496BtiVFjhPw+5pkEmNuz+Pehv73KGJoYtvtf6OZgzaJ8kL8mKpiQxHn0ukOkIkoKwRJZV6F48Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T22:35:45.757492Z"},"content_sha256":"0ab1089ca6a9dbd82c358281022c34805fd016e8184f15a710a3f983e6ec2455","schema_version":"1.0","event_id":"sha256:0ab1089ca6a9dbd82c358281022c34805fd016e8184f15a710a3f983e6ec2455"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:7QEA7XDJWUPA576W2ZJSVEPVS7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Coarse Is Better? A New Pipeline Towards Self-Supervised Learning with Uncurated Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jianxin Wu, Ke Zhu, Yin-Yin He","submitted_at":"2023-06-07T08:35:27Z","abstract_excerpt":"Most self-supervised learning (SSL) methods often work on curated datasets where the object-centric assumption holds. This assumption breaks down in uncurated images. Existing scene image SSL methods try to find the two views from original scene images that are well matched or dense, which is both complex and computationally heavy. This paper proposes a conceptually different pipeline: first find regions that are coarse objects (with adequate objectness), crop them out as pseudo object-centric images, then any SSL method can be directly applied as in a real object-centric dataset. That is, coa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.04244","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/2306.04244/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":"2026-07-05T06:55:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Us7cGsTqw7L84sHQGItUKFFwlE0U+b6CImYe/t7OwcVvspFtPsTUYAu6uoA0cUiPG1wre9GW5N7i9AbKcZq5Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T22:35:45.757870Z"},"content_sha256":"5f73bca1e646b548c83eca5ac56e128156128652c25f473ff6f6b0db9f41a3fe","schema_version":"1.0","event_id":"sha256:5f73bca1e646b548c83eca5ac56e128156128652c25f473ff6f6b0db9f41a3fe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7QEA7XDJWUPA576W2ZJSVEPVS7/bundle.json","state_url":"https://pith.science/pith/7QEA7XDJWUPA576W2ZJSVEPVS7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7QEA7XDJWUPA576W2ZJSVEPVS7/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":"2026-08-12T22:35:45Z","links":{"resolver":"https://pith.science/pith/7QEA7XDJWUPA576W2ZJSVEPVS7","bundle":"https://pith.science/pith/7QEA7XDJWUPA576W2ZJSVEPVS7/bundle.json","state":"https://pith.science/pith/7QEA7XDJWUPA576W2ZJSVEPVS7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7QEA7XDJWUPA576W2ZJSVEPVS7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:7QEA7XDJWUPA576W2ZJSVEPVS7","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":"29cbc2a9413d22341d4d1b93d02b2b3530bb44de9bbda210335013b5f73f7dfe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-07T08:35:27Z","title_canon_sha256":"051086fd6877407b68a4d8ddb9b78f3b8a674d0ac2558ebff0fca21c095e183d"},"schema_version":"1.0","source":{"id":"2306.04244","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.04244","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"arxiv_version","alias_value":"2306.04244v3","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.04244","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"pith_short_12","alias_value":"7QEA7XDJWUPA","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"pith_short_16","alias_value":"7QEA7XDJWUPA576W","created_at":"2026-07-05T06:55:23Z"},{"alias_kind":"pith_short_8","alias_value":"7QEA7XDJ","created_at":"2026-07-05T06:55:23Z"}],"graph_snapshots":[{"event_id":"sha256:5f73bca1e646b548c83eca5ac56e128156128652c25f473ff6f6b0db9f41a3fe","target":"graph","created_at":"2026-07-05T06:55:23Z","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/2306.04244/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most self-supervised learning (SSL) methods often work on curated datasets where the object-centric assumption holds. This assumption breaks down in uncurated images. Existing scene image SSL methods try to find the two views from original scene images that are well matched or dense, which is both complex and computationally heavy. This paper proposes a conceptually different pipeline: first find regions that are coarse objects (with adequate objectness), crop them out as pseudo object-centric images, then any SSL method can be directly applied as in a real object-centric dataset. That is, coa","authors_text":"Jianxin Wu, Ke Zhu, Yin-Yin He","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-07T08:35:27Z","title":"Coarse Is Better? A New Pipeline Towards Self-Supervised Learning with Uncurated Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.04244","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":"sha256:0ab1089ca6a9dbd82c358281022c34805fd016e8184f15a710a3f983e6ec2455","target":"record","created_at":"2026-07-05T06:55:23Z","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":"29cbc2a9413d22341d4d1b93d02b2b3530bb44de9bbda210335013b5f73f7dfe","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-07T08:35:27Z","title_canon_sha256":"051086fd6877407b68a4d8ddb9b78f3b8a674d0ac2558ebff0fca21c095e183d"},"schema_version":"1.0","source":{"id":"2306.04244","kind":"arxiv","version":3}},"canonical_sha256":"fc080fdc69b51e0effd6d6532a91f597e2b8c28d46417836e5ec751da9d6f848","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fc080fdc69b51e0effd6d6532a91f597e2b8c28d46417836e5ec751da9d6f848","first_computed_at":"2026-07-05T06:55:23.863424Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:55:23.863424Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UlPLVZ/fyzGzaCttyR2gi0vBxYAo81Nu5NV2Y5+Hif1VDu0Fuk5No3m38Q7xNwu01/e3CWZOJywbDUwDKLuEDg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:55:23.863885Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.04244","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ab1089ca6a9dbd82c358281022c34805fd016e8184f15a710a3f983e6ec2455","sha256:5f73bca1e646b548c83eca5ac56e128156128652c25f473ff6f6b0db9f41a3fe"],"state_sha256":"7ee84549e26ce7147eaa8b02b9e7ff302d68f3ad8ddf5bbc1c004a880f185297"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n20iCe0yEKdAYKMRZMMtT6OZM7o0SDV/giUcIWEp76l+pUsdPjOUo1HcJneNj5c8vyY06JkJprOB8FfpSIHaAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T22:35:45.760184Z","bundle_sha256":"62313e5b8709c7a937ea6c5c50d013e3d4349290e802f9f45570eadf06392f8b"}}