{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:ZRYRDOOMTH4PVSXQN76ZXZKKYI","short_pith_number":"pith:ZRYRDOOM","canonical_record":{"source":{"id":"1611.06962","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2016-11-21T19:24:58Z","cross_cats_sorted":[],"title_canon_sha256":"91d7e507b08ab35ee1bb28057d8cf35eedacd4f4fb7a7f506b88f8b3cc3afc17","abstract_canon_sha256":"a14e1b841355a89f97b91871834abc7057153ab75c7a37c7e8d97ddc513ed266"},"schema_version":"1.0"},"canonical_sha256":"cc7111b9cc99f8facaf06ffd9be54ac2137b948a46346eeafffed4d3c408f4a6","source":{"kind":"arxiv","id":"1611.06962","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.06962","created_at":"2026-05-18T00:56:00Z"},{"alias_kind":"arxiv_version","alias_value":"1611.06962v3","created_at":"2026-05-18T00:56:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.06962","created_at":"2026-05-18T00:56:00Z"},{"alias_kind":"pith_short_12","alias_value":"ZRYRDOOMTH4P","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"ZRYRDOOMTH4PVSXQ","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"ZRYRDOOM","created_at":"2026-05-18T12:30:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:ZRYRDOOMTH4PVSXQN76ZXZKKYI","target":"record","payload":{"canonical_record":{"source":{"id":"1611.06962","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2016-11-21T19:24:58Z","cross_cats_sorted":[],"title_canon_sha256":"91d7e507b08ab35ee1bb28057d8cf35eedacd4f4fb7a7f506b88f8b3cc3afc17","abstract_canon_sha256":"a14e1b841355a89f97b91871834abc7057153ab75c7a37c7e8d97ddc513ed266"},"schema_version":"1.0"},"canonical_sha256":"cc7111b9cc99f8facaf06ffd9be54ac2137b948a46346eeafffed4d3c408f4a6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:56:00.118588Z","signature_b64":"78aDwZeNsr3AXzWUF4cGEprMt9XkrDzGvh50Qr2EgXdGNAiV8PcIIqubaxQVAjIR3ROASfh40gf9wpye9QETBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cc7111b9cc99f8facaf06ffd9be54ac2137b948a46346eeafffed4d3c408f4a6","last_reissued_at":"2026-05-18T00:56:00.118102Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:56:00.118102Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1611.06962","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":"2026-05-18T00:56:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4bPBwExIYA6goP1NmAm3WpOxLV0lvWfxiM1FeuM/X95ySDCRWHr5XU1FOiy3pVY3gIAkaCjS5cFU+7QLtN+KDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T19:58:16.384861Z"},"content_sha256":"593c923a5f8a054fca09db0d361bceba99a9a092b2bdab0adc4271d249b3e597","schema_version":"1.0","event_id":"sha256:593c923a5f8a054fca09db0d361bceba99a9a092b2bdab0adc4271d249b3e597"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:ZRYRDOOMTH4PVSXQN76ZXZKKYI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sampled Image Tagging and Retrieval Methods on User Generated Content","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alex Gude, Barry Chen, Carmen Carrano, Charles Foster, Karl Ni, Kyle Zaragoza, Yonas Tesfaye","submitted_at":"2016-11-21T19:24:58Z","abstract_excerpt":"Traditional image tagging and retrieval algorithms have limited value as a result of being trained with heavily curated datasets. These limitations are most evident when arbitrary search words are used that do not intersect with training set labels. Weak labels from user generated content (UGC) found in the wild (e.g., Google Photos, FlickR, etc.) have an almost unlimited number of unique words in the metadata tags. Prior work on word embeddings successfully leveraged unstructured text with large vocabularies, and our proposed method seeks to apply similar cost functions to open source imagery"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.06962","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":""},"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":"2026-05-18T00:56:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G5DIsCsgcpQPVRrrMsC7T+Oq7r7i5IjSMgHz4EE+HosxVWLqtOqYgA9tZmaI/DZEKunu4S8nVFEcASijPPyKBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T19:58:16.385198Z"},"content_sha256":"d37bd9e2d66df610c9490f086024e3f05f949737532eaf3513964b6a6d78b64e","schema_version":"1.0","event_id":"sha256:d37bd9e2d66df610c9490f086024e3f05f949737532eaf3513964b6a6d78b64e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZRYRDOOMTH4PVSXQN76ZXZKKYI/bundle.json","state_url":"https://pith.science/pith/ZRYRDOOMTH4PVSXQN76ZXZKKYI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZRYRDOOMTH4PVSXQN76ZXZKKYI/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":"2026-06-01T19:58:16Z","links":{"resolver":"https://pith.science/pith/ZRYRDOOMTH4PVSXQN76ZXZKKYI","bundle":"https://pith.science/pith/ZRYRDOOMTH4PVSXQN76ZXZKKYI/bundle.json","state":"https://pith.science/pith/ZRYRDOOMTH4PVSXQN76ZXZKKYI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZRYRDOOMTH4PVSXQN76ZXZKKYI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:ZRYRDOOMTH4PVSXQN76ZXZKKYI","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":"a14e1b841355a89f97b91871834abc7057153ab75c7a37c7e8d97ddc513ed266","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2016-11-21T19:24:58Z","title_canon_sha256":"91d7e507b08ab35ee1bb28057d8cf35eedacd4f4fb7a7f506b88f8b3cc3afc17"},"schema_version":"1.0","source":{"id":"1611.06962","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.06962","created_at":"2026-05-18T00:56:00Z"},{"alias_kind":"arxiv_version","alias_value":"1611.06962v3","created_at":"2026-05-18T00:56:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.06962","created_at":"2026-05-18T00:56:00Z"},{"alias_kind":"pith_short_12","alias_value":"ZRYRDOOMTH4P","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"ZRYRDOOMTH4PVSXQ","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"ZRYRDOOM","created_at":"2026-05-18T12:30:55Z"}],"graph_snapshots":[{"event_id":"sha256:d37bd9e2d66df610c9490f086024e3f05f949737532eaf3513964b6a6d78b64e","target":"graph","created_at":"2026-05-18T00:56:00Z","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"},"paper":{"abstract_excerpt":"Traditional image tagging and retrieval algorithms have limited value as a result of being trained with heavily curated datasets. These limitations are most evident when arbitrary search words are used that do not intersect with training set labels. Weak labels from user generated content (UGC) found in the wild (e.g., Google Photos, FlickR, etc.) have an almost unlimited number of unique words in the metadata tags. Prior work on word embeddings successfully leveraged unstructured text with large vocabularies, and our proposed method seeks to apply similar cost functions to open source imagery","authors_text":"Alex Gude, Barry Chen, Carmen Carrano, Charles Foster, Karl Ni, Kyle Zaragoza, Yonas Tesfaye","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2016-11-21T19:24:58Z","title":"Sampled Image Tagging and Retrieval Methods on User Generated Content"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.06962","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":"sha256:593c923a5f8a054fca09db0d361bceba99a9a092b2bdab0adc4271d249b3e597","target":"record","created_at":"2026-05-18T00:56:00Z","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":"a14e1b841355a89f97b91871834abc7057153ab75c7a37c7e8d97ddc513ed266","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2016-11-21T19:24:58Z","title_canon_sha256":"91d7e507b08ab35ee1bb28057d8cf35eedacd4f4fb7a7f506b88f8b3cc3afc17"},"schema_version":"1.0","source":{"id":"1611.06962","kind":"arxiv","version":3}},"canonical_sha256":"cc7111b9cc99f8facaf06ffd9be54ac2137b948a46346eeafffed4d3c408f4a6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc7111b9cc99f8facaf06ffd9be54ac2137b948a46346eeafffed4d3c408f4a6","first_computed_at":"2026-05-18T00:56:00.118102Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:56:00.118102Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"78aDwZeNsr3AXzWUF4cGEprMt9XkrDzGvh50Qr2EgXdGNAiV8PcIIqubaxQVAjIR3ROASfh40gf9wpye9QETBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:56:00.118588Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.06962","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:593c923a5f8a054fca09db0d361bceba99a9a092b2bdab0adc4271d249b3e597","sha256:d37bd9e2d66df610c9490f086024e3f05f949737532eaf3513964b6a6d78b64e"],"state_sha256":"a828314b854ec6ffd3f46a3a9c4e6bf452f061f1cf53d02bcdc1a88965ff7464"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"keSGNUQrvR43NnfLhSSwSjTQM1tVirPVTAtUrCxiHa49I8yg4851yqjHI/orBrxRGylBinUaZGeeP4UUNZiZCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T19:58:16.387490Z","bundle_sha256":"cd01f9adf16f40b6dadd118850d4c7ec93d0478a6d17135441f8df595a5f3450"}}