{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:5NSOEJD7TTXMJ5FBRBNZTXSDRJ","short_pith_number":"pith:5NSOEJD7","canonical_record":{"source":{"id":"2307.05435","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-11T16:57:17Z","cross_cats_sorted":[],"title_canon_sha256":"4213e9a9522b8b03e2a9cbb9f8fe2724bb6ec50c10fc1ccdb3ed46f0e38e12b7","abstract_canon_sha256":"51335dca3af142f6858e769d8dad686848dc3f09dddb4234d2863fcfa201ce19"},"schema_version":"1.0"},"canonical_sha256":"eb64e2247f9ceec4f4a1885b99de438a4686c81e2595d8ee86ecd93462c31cab","source":{"kind":"arxiv","id":"2307.05435","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.05435","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"arxiv_version","alias_value":"2307.05435v4","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.05435","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"pith_short_12","alias_value":"5NSOEJD7TTXM","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"pith_short_16","alias_value":"5NSOEJD7TTXMJ5FB","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"pith_short_8","alias_value":"5NSOEJD7","created_at":"2026-07-05T09:23:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:5NSOEJD7TTXMJ5FBRBNZTXSDRJ","target":"record","payload":{"canonical_record":{"source":{"id":"2307.05435","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-11T16:57:17Z","cross_cats_sorted":[],"title_canon_sha256":"4213e9a9522b8b03e2a9cbb9f8fe2724bb6ec50c10fc1ccdb3ed46f0e38e12b7","abstract_canon_sha256":"51335dca3af142f6858e769d8dad686848dc3f09dddb4234d2863fcfa201ce19"},"schema_version":"1.0"},"canonical_sha256":"eb64e2247f9ceec4f4a1885b99de438a4686c81e2595d8ee86ecd93462c31cab","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:23:32.772643Z","signature_b64":"cnLqh9mFTC7YvV+ohG39agtSGyYP3fVlrUcAk31cqac3jieZJ7Sb294aAu0ZxdfjNUGTqQmLgTAMmnlcDAwhDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eb64e2247f9ceec4f4a1885b99de438a4686c81e2595d8ee86ecd93462c31cab","last_reissued_at":"2026-07-05T09:23:32.772134Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:23:32.772134Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.05435","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:23:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ciyCMC2J+MUJFt+hlALwqqqqi9SdVWRE2EQ/pUlw8rnpBUvUXedJgBHk884NC1tIrwbjWbQp79ll/MhIXRv1Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T01:34:00.372566Z"},"content_sha256":"380574a2f5378fd34f46ac6ac6ffe7891e25344a5a14e12e5d408c054671697c","schema_version":"1.0","event_id":"sha256:380574a2f5378fd34f46ac6ac6ffe7891e25344a5a14e12e5d408c054671697c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:5NSOEJD7TTXMJ5FBRBNZTXSDRJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Akira Nair, Carsten Eickhoff, Eric Han, Eva Schiller, Michal Golovanevsky, Ritambhara Singh","submitted_at":"2023-07-11T16:57:17Z","abstract_excerpt":"Multimodal learning models have become increasingly important as they surpass single-modality approaches on diverse tasks ranging from question-answering to autonomous driving. Despite the importance of multimodal learning, existing efforts focus on NLP applications, where the number of modalities is typically less than four (audio, video, text, images). However, data inputs in other domains, such as the medical field, may include X-rays, PET scans, MRIs, genetic screening, clinical notes, and more, creating a need for both efficient and accurate information fusion. Many state-of-the-art model"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.05435","kind":"arxiv","version":4},"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/2307.05435/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":"2026-07-05T09:23:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LFiia5eEXpxq7thVf5+R3J8nPxuQkCqn7LXrO1SfdXNfUZe+vEsA9CiqMCiluSsTfcSpl86Zrv2Vecc70l4KAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T01:34:00.372955Z"},"content_sha256":"6aeff6658201806a82240f00d353c99f94269c96198fac1ca3b5e5ad3072d6e6","schema_version":"1.0","event_id":"sha256:6aeff6658201806a82240f00d353c99f94269c96198fac1ca3b5e5ad3072d6e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5NSOEJD7TTXMJ5FBRBNZTXSDRJ/bundle.json","state_url":"https://pith.science/pith/5NSOEJD7TTXMJ5FBRBNZTXSDRJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5NSOEJD7TTXMJ5FBRBNZTXSDRJ/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":"2026-08-05T01:34:00Z","links":{"resolver":"https://pith.science/pith/5NSOEJD7TTXMJ5FBRBNZTXSDRJ","bundle":"https://pith.science/pith/5NSOEJD7TTXMJ5FBRBNZTXSDRJ/bundle.json","state":"https://pith.science/pith/5NSOEJD7TTXMJ5FBRBNZTXSDRJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5NSOEJD7TTXMJ5FBRBNZTXSDRJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5NSOEJD7TTXMJ5FBRBNZTXSDRJ","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":"51335dca3af142f6858e769d8dad686848dc3f09dddb4234d2863fcfa201ce19","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-11T16:57:17Z","title_canon_sha256":"4213e9a9522b8b03e2a9cbb9f8fe2724bb6ec50c10fc1ccdb3ed46f0e38e12b7"},"schema_version":"1.0","source":{"id":"2307.05435","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.05435","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"arxiv_version","alias_value":"2307.05435v4","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.05435","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"pith_short_12","alias_value":"5NSOEJD7TTXM","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"pith_short_16","alias_value":"5NSOEJD7TTXMJ5FB","created_at":"2026-07-05T09:23:32Z"},{"alias_kind":"pith_short_8","alias_value":"5NSOEJD7","created_at":"2026-07-05T09:23:32Z"}],"graph_snapshots":[{"event_id":"sha256:6aeff6658201806a82240f00d353c99f94269c96198fac1ca3b5e5ad3072d6e6","target":"graph","created_at":"2026-07-05T09:23:32Z","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/2307.05435/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal learning models have become increasingly important as they surpass single-modality approaches on diverse tasks ranging from question-answering to autonomous driving. Despite the importance of multimodal learning, existing efforts focus on NLP applications, where the number of modalities is typically less than four (audio, video, text, images). However, data inputs in other domains, such as the medical field, may include X-rays, PET scans, MRIs, genetic screening, clinical notes, and more, creating a need for both efficient and accurate information fusion. Many state-of-the-art model","authors_text":"Akira Nair, Carsten Eickhoff, Eric Han, Eva Schiller, Michal Golovanevsky, Ritambhara Singh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-11T16:57:17Z","title":"One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.05435","kind":"arxiv","version":4},"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":"sha256:380574a2f5378fd34f46ac6ac6ffe7891e25344a5a14e12e5d408c054671697c","target":"record","created_at":"2026-07-05T09:23:32Z","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":"51335dca3af142f6858e769d8dad686848dc3f09dddb4234d2863fcfa201ce19","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-11T16:57:17Z","title_canon_sha256":"4213e9a9522b8b03e2a9cbb9f8fe2724bb6ec50c10fc1ccdb3ed46f0e38e12b7"},"schema_version":"1.0","source":{"id":"2307.05435","kind":"arxiv","version":4}},"canonical_sha256":"eb64e2247f9ceec4f4a1885b99de438a4686c81e2595d8ee86ecd93462c31cab","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eb64e2247f9ceec4f4a1885b99de438a4686c81e2595d8ee86ecd93462c31cab","first_computed_at":"2026-07-05T09:23:32.772134Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:23:32.772134Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cnLqh9mFTC7YvV+ohG39agtSGyYP3fVlrUcAk31cqac3jieZJ7Sb294aAu0ZxdfjNUGTqQmLgTAMmnlcDAwhDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:23:32.772643Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.05435","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:380574a2f5378fd34f46ac6ac6ffe7891e25344a5a14e12e5d408c054671697c","sha256:6aeff6658201806a82240f00d353c99f94269c96198fac1ca3b5e5ad3072d6e6"],"state_sha256":"287465ce33d72eda9f1d5db49ba18b9693c2fb498df450491a700c6d1535ae34"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D/3P+JyeaUXfNNr3CB87b0KEOQNKnD9+Tj8UusBniNpBadx2lCGVBE4SOd+Z2Rt6Slqa1s1r2fBCte+S+FqpAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T01:34:00.375454Z","bundle_sha256":"46f1792c527b424fafc5735e58c2f5cc86408a9c88e7aab814a4de815fa38cf6"}}