{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:3N6OXDBXLHCXB2KFZ4RIW4WKAO","short_pith_number":"pith:3N6OXDBX","canonical_record":{"source":{"id":"1904.05709","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-11T14:10:53Z","cross_cats_sorted":[],"title_canon_sha256":"b4329eab6f357e95c0563c5d24d5ec1f8922e8bdb6df9a530747bef55595dd71","abstract_canon_sha256":"5a717da34a096c5241d916888ff9b1148953f918b41e0495dc62b84cdbca966e"},"schema_version":"1.0"},"canonical_sha256":"db7ceb8c3759c570e945cf228b72ca03976ecdd847cbe55a53c57c155532e953","source":{"kind":"arxiv","id":"1904.05709","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.05709","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"arxiv_version","alias_value":"1904.05709v2","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.05709","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"pith_short_12","alias_value":"3N6OXDBXLHCX","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"pith_short_16","alias_value":"3N6OXDBXLHCXB2KF","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"pith_short_8","alias_value":"3N6OXDBX","created_at":"2026-07-05T01:06:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:3N6OXDBXLHCXB2KFZ4RIW4WKAO","target":"record","payload":{"canonical_record":{"source":{"id":"1904.05709","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-11T14:10:53Z","cross_cats_sorted":[],"title_canon_sha256":"b4329eab6f357e95c0563c5d24d5ec1f8922e8bdb6df9a530747bef55595dd71","abstract_canon_sha256":"5a717da34a096c5241d916888ff9b1148953f918b41e0495dc62b84cdbca966e"},"schema_version":"1.0"},"canonical_sha256":"db7ceb8c3759c570e945cf228b72ca03976ecdd847cbe55a53c57c155532e953","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:06:07.529749Z","signature_b64":"84ZeVLEnivAGrbKi0dk7sYu43LfJ0gbUny0iMgCJVQK3KtUQPXsYImYSCVY1QGRdPT9yvkj/zSo6A4oXu/NuBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db7ceb8c3759c570e945cf228b72ca03976ecdd847cbe55a53c57c155532e953","last_reissued_at":"2026-07-05T01:06:07.529335Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:06:07.529335Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.05709","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":"2026-07-05T01:06:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ibCAQeXHkXj5EXPnzIWJUrGaHC7nvWsAVmeCOK7KFLyNOQLc/EeQzzUDlrUS5ZVloAOQqbm6ClTZ5RT6h96qAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T15:52:29.539345Z"},"content_sha256":"b9145f037d546acc80b4dca89125807251200d1dcf4bff14fcbd17ffbb3c88bd","schema_version":"1.0","event_id":"sha256:b9145f037d546acc80b4dca89125807251200d1dcf4bff14fcbd17ffbb3c88bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:3N6OXDBXLHCXB2KFZ4RIW4WKAO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Elucidating image-to-set prediction: An analysis of models, losses and datasets","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Adriana Romero, Amaia Salvador, Luis Pineda, Michal Drozdzal","submitted_at":"2019-04-11T14:10:53Z","abstract_excerpt":"In this paper, we identify an important reproducibility challenge in the image-to-set prediction literature that impedes proper comparisons among published methods, namely, researchers use different evaluation protocols to assess their contributions. To alleviate this issue, we introduce an image-to-set prediction benchmark suite built on top of five public datasets of increasing task complexity that are suitable for multi-label classification (VOC, COCO, NUS-WIDE, ADE20k and Recipe1M). Using the benchmark, we provide an in-depth analysis where we study the key components of current models, na"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.05709","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/1904.05709/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":"2026-07-05T01:06:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zmUhVTeSK8MG7q8bLjXIP6rEwu0g+cqn8IFK7ZEgP8ZgkIbONIbJ7W3IXww+Ve+0JdNNrHSku210ZN52OZxlDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T15:52:29.539894Z"},"content_sha256":"43b233e9f9588c46e758790d22404f5c4a31a804d5dd9091f53d23b4fb0485f0","schema_version":"1.0","event_id":"sha256:43b233e9f9588c46e758790d22404f5c4a31a804d5dd9091f53d23b4fb0485f0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3N6OXDBXLHCXB2KFZ4RIW4WKAO/bundle.json","state_url":"https://pith.science/pith/3N6OXDBXLHCXB2KFZ4RIW4WKAO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3N6OXDBXLHCXB2KFZ4RIW4WKAO/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":"2026-08-08T15:52:29Z","links":{"resolver":"https://pith.science/pith/3N6OXDBXLHCXB2KFZ4RIW4WKAO","bundle":"https://pith.science/pith/3N6OXDBXLHCXB2KFZ4RIW4WKAO/bundle.json","state":"https://pith.science/pith/3N6OXDBXLHCXB2KFZ4RIW4WKAO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3N6OXDBXLHCXB2KFZ4RIW4WKAO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:3N6OXDBXLHCXB2KFZ4RIW4WKAO","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":"5a717da34a096c5241d916888ff9b1148953f918b41e0495dc62b84cdbca966e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-11T14:10:53Z","title_canon_sha256":"b4329eab6f357e95c0563c5d24d5ec1f8922e8bdb6df9a530747bef55595dd71"},"schema_version":"1.0","source":{"id":"1904.05709","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.05709","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"arxiv_version","alias_value":"1904.05709v2","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.05709","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"pith_short_12","alias_value":"3N6OXDBXLHCX","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"pith_short_16","alias_value":"3N6OXDBXLHCXB2KF","created_at":"2026-07-05T01:06:07Z"},{"alias_kind":"pith_short_8","alias_value":"3N6OXDBX","created_at":"2026-07-05T01:06:07Z"}],"graph_snapshots":[{"event_id":"sha256:43b233e9f9588c46e758790d22404f5c4a31a804d5dd9091f53d23b4fb0485f0","target":"graph","created_at":"2026-07-05T01:06:07Z","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/1904.05709/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we identify an important reproducibility challenge in the image-to-set prediction literature that impedes proper comparisons among published methods, namely, researchers use different evaluation protocols to assess their contributions. To alleviate this issue, we introduce an image-to-set prediction benchmark suite built on top of five public datasets of increasing task complexity that are suitable for multi-label classification (VOC, COCO, NUS-WIDE, ADE20k and Recipe1M). Using the benchmark, we provide an in-depth analysis where we study the key components of current models, na","authors_text":"Adriana Romero, Amaia Salvador, Luis Pineda, Michal Drozdzal","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-11T14:10:53Z","title":"Elucidating image-to-set prediction: An analysis of models, losses and datasets"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.05709","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:b9145f037d546acc80b4dca89125807251200d1dcf4bff14fcbd17ffbb3c88bd","target":"record","created_at":"2026-07-05T01:06:07Z","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":"5a717da34a096c5241d916888ff9b1148953f918b41e0495dc62b84cdbca966e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-11T14:10:53Z","title_canon_sha256":"b4329eab6f357e95c0563c5d24d5ec1f8922e8bdb6df9a530747bef55595dd71"},"schema_version":"1.0","source":{"id":"1904.05709","kind":"arxiv","version":2}},"canonical_sha256":"db7ceb8c3759c570e945cf228b72ca03976ecdd847cbe55a53c57c155532e953","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"db7ceb8c3759c570e945cf228b72ca03976ecdd847cbe55a53c57c155532e953","first_computed_at":"2026-07-05T01:06:07.529335Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:06:07.529335Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"84ZeVLEnivAGrbKi0dk7sYu43LfJ0gbUny0iMgCJVQK3KtUQPXsYImYSCVY1QGRdPT9yvkj/zSo6A4oXu/NuBA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:06:07.529749Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.05709","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b9145f037d546acc80b4dca89125807251200d1dcf4bff14fcbd17ffbb3c88bd","sha256:43b233e9f9588c46e758790d22404f5c4a31a804d5dd9091f53d23b4fb0485f0"],"state_sha256":"99cb20518c5c424a7b94bedbe868b917eb26bd76f666a43a6c6b38fe19d79e32"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"srn5T+R14vTKclbx24YrbXvozLihdVUAqemoGCAEamfcor3A2EXa6DnFCbyOXyyJUMp0k6CWf1lQ5MY1zRj7Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T15:52:29.543434Z","bundle_sha256":"311503d7581ac5d2228506b5addd0ecaffb231e56539383b91a84a8d95c9fe9e"}}