{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:WZOBOHHOTP4BYSDODJ2Z2KRHYW","short_pith_number":"pith:WZOBOHHO","canonical_record":{"source":{"id":"1810.06553","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-14T20:51:41Z","cross_cats_sorted":[],"title_canon_sha256":"2471cf640253e75c34a8cea4dbf832ae277458ab5077f3927a5db2aba61bde14","abstract_canon_sha256":"c313b99c39fb74a006f0a6c75e43c2cbb428f3e8f9aaefdca005bcf3a5bdb404"},"schema_version":"1.0"},"canonical_sha256":"b65c171cee9bf81c486e1a759d2a27c5aec1b2e9c7ff9bcb01fe3b70f2236d8c","source":{"kind":"arxiv","id":"1810.06553","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.06553","created_at":"2026-05-17T23:41:02Z"},{"alias_kind":"arxiv_version","alias_value":"1810.06553v2","created_at":"2026-05-17T23:41:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.06553","created_at":"2026-05-17T23:41:02Z"},{"alias_kind":"pith_short_12","alias_value":"WZOBOHHOTP4B","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WZOBOHHOTP4BYSDO","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WZOBOHHO","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:WZOBOHHOTP4BYSDODJ2Z2KRHYW","target":"record","payload":{"canonical_record":{"source":{"id":"1810.06553","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-14T20:51:41Z","cross_cats_sorted":[],"title_canon_sha256":"2471cf640253e75c34a8cea4dbf832ae277458ab5077f3927a5db2aba61bde14","abstract_canon_sha256":"c313b99c39fb74a006f0a6c75e43c2cbb428f3e8f9aaefdca005bcf3a5bdb404"},"schema_version":"1.0"},"canonical_sha256":"b65c171cee9bf81c486e1a759d2a27c5aec1b2e9c7ff9bcb01fe3b70f2236d8c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:02.305104Z","signature_b64":"Mk7liMGWXCzWaqM/gr2UhB3vnf/4VsGFchT/Gk7S0YSYxAV9snp0WPfJ/FI5WaIEQwLvDjCuUQTpeI0iNDl6Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b65c171cee9bf81c486e1a759d2a27c5aec1b2e9c7ff9bcb01fe3b70f2236d8c","last_reissued_at":"2026-05-17T23:41:02.304533Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:02.304533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.06553","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":"2026-05-17T23:41:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7d1CfQgw3AY3W3jZBz+3dmKO2oBe4Ifrkk9f4Ij/V2sSZcbF5j2vSzI919Acl0jMjhQwy4RsCoHc0rAVa9kyAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T07:28:59.779745Z"},"content_sha256":"924d29b2fd63b91a46d48bb6d5b62e092aa5e30b5e1f2b606be32f855cac3364","schema_version":"1.0","event_id":"sha256:924d29b2fd63b91a46d48bb6d5b62e092aa5e30b5e1f2b606be32f855cac3364"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:WZOBOHHOTP4BYSDODJ2Z2KRHYW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amaia Salvador, Antonio Torralba, Aritro Biswas, Ferda Ofli, Ingmar Weber, Javier Marin, Nicholas Hynes, Yusuf Aytar","submitted_at":"2018-10-14T20:51:41Z","abstract_excerpt":"In this paper, we introduce Recipe1M+, a new large-scale, structured corpus of over one million cooking recipes and 13 million food images. As the largest publicly available collection of recipe data, Recipe1M+ affords the ability to train high-capacity modelson aligned, multimodal data. Using these data, we train a neural network to learn a joint embedding of recipes and images that yields impressive results on an image-recipe retrieval task. Moreover, we demonstrate that regularization via the addition of a high-level classification objective both improves retrieval performance to rival that"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.06553","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":""},"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":"2026-05-17T23:41:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o3J7xm5ldFwFLpV0XBvDyTVrhG0EmLhOPllEN+LPZxDm3T8ruI5sRwTrBbWWzKxP3KXgEwoVqCWKdQpvDm8bAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T07:28:59.780372Z"},"content_sha256":"04139b48356a4a51c658d8eb9181159c19b7119fd6ae29d03d3b6f7d99862ffc","schema_version":"1.0","event_id":"sha256:04139b48356a4a51c658d8eb9181159c19b7119fd6ae29d03d3b6f7d99862ffc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WZOBOHHOTP4BYSDODJ2Z2KRHYW/bundle.json","state_url":"https://pith.science/pith/WZOBOHHOTP4BYSDODJ2Z2KRHYW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WZOBOHHOTP4BYSDODJ2Z2KRHYW/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":"2026-05-27T07:28:59Z","links":{"resolver":"https://pith.science/pith/WZOBOHHOTP4BYSDODJ2Z2KRHYW","bundle":"https://pith.science/pith/WZOBOHHOTP4BYSDODJ2Z2KRHYW/bundle.json","state":"https://pith.science/pith/WZOBOHHOTP4BYSDODJ2Z2KRHYW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WZOBOHHOTP4BYSDODJ2Z2KRHYW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WZOBOHHOTP4BYSDODJ2Z2KRHYW","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":"c313b99c39fb74a006f0a6c75e43c2cbb428f3e8f9aaefdca005bcf3a5bdb404","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-14T20:51:41Z","title_canon_sha256":"2471cf640253e75c34a8cea4dbf832ae277458ab5077f3927a5db2aba61bde14"},"schema_version":"1.0","source":{"id":"1810.06553","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.06553","created_at":"2026-05-17T23:41:02Z"},{"alias_kind":"arxiv_version","alias_value":"1810.06553v2","created_at":"2026-05-17T23:41:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.06553","created_at":"2026-05-17T23:41:02Z"},{"alias_kind":"pith_short_12","alias_value":"WZOBOHHOTP4B","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WZOBOHHOTP4BYSDO","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WZOBOHHO","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:04139b48356a4a51c658d8eb9181159c19b7119fd6ae29d03d3b6f7d99862ffc","target":"graph","created_at":"2026-05-17T23:41:02Z","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":"In this paper, we introduce Recipe1M+, a new large-scale, structured corpus of over one million cooking recipes and 13 million food images. As the largest publicly available collection of recipe data, Recipe1M+ affords the ability to train high-capacity modelson aligned, multimodal data. Using these data, we train a neural network to learn a joint embedding of recipes and images that yields impressive results on an image-recipe retrieval task. Moreover, we demonstrate that regularization via the addition of a high-level classification objective both improves retrieval performance to rival that","authors_text":"Amaia Salvador, Antonio Torralba, Aritro Biswas, Ferda Ofli, Ingmar Weber, Javier Marin, Nicholas Hynes, Yusuf Aytar","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-14T20:51:41Z","title":"Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.06553","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":"sha256:924d29b2fd63b91a46d48bb6d5b62e092aa5e30b5e1f2b606be32f855cac3364","target":"record","created_at":"2026-05-17T23:41:02Z","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":"c313b99c39fb74a006f0a6c75e43c2cbb428f3e8f9aaefdca005bcf3a5bdb404","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-14T20:51:41Z","title_canon_sha256":"2471cf640253e75c34a8cea4dbf832ae277458ab5077f3927a5db2aba61bde14"},"schema_version":"1.0","source":{"id":"1810.06553","kind":"arxiv","version":2}},"canonical_sha256":"b65c171cee9bf81c486e1a759d2a27c5aec1b2e9c7ff9bcb01fe3b70f2236d8c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b65c171cee9bf81c486e1a759d2a27c5aec1b2e9c7ff9bcb01fe3b70f2236d8c","first_computed_at":"2026-05-17T23:41:02.304533Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:41:02.304533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Mk7liMGWXCzWaqM/gr2UhB3vnf/4VsGFchT/Gk7S0YSYxAV9snp0WPfJ/FI5WaIEQwLvDjCuUQTpeI0iNDl6Bg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:41:02.305104Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.06553","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:924d29b2fd63b91a46d48bb6d5b62e092aa5e30b5e1f2b606be32f855cac3364","sha256:04139b48356a4a51c658d8eb9181159c19b7119fd6ae29d03d3b6f7d99862ffc"],"state_sha256":"f0c7ba9245e0f1ca14f237e70b20300baaac2d05cbeba735379bef487ef8bece"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nqMCMMJcNnzaJtHHRZiOHXLTCixAmSYnZkBIpIbGkTAzOdpRKW8fa7R/9hEDDgNTWdlhI6aCofB5quepgbZQAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T07:28:59.782872Z","bundle_sha256":"e2f93359a9aacc0653600a8c9ab26d2dc6fee3065b2af4e304802ac9c30c12ae"}}