{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:UIJNBKVRUJKAXU36XK4NMI2JGW","short_pith_number":"pith:UIJNBKVR","canonical_record":{"source":{"id":"2104.01394","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-03T13:01:19Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"fe8e59a889eb098c2f18b25960967d8f0006e3b6665fcb9814bce094ba5f1e73","abstract_canon_sha256":"9d0b50a2d77a77c2a72f54230378bc2476837225b18c09bf30e9bd91a9fbe3bd"},"schema_version":"1.0"},"canonical_sha256":"a212d0aab1a2540bd37ebab8d62349359764eb8fbcf71611e43b773f8f40a4e3","source":{"kind":"arxiv","id":"2104.01394","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.01394","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"arxiv_version","alias_value":"2104.01394v1","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.01394","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"pith_short_12","alias_value":"UIJNBKVRUJKA","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"pith_short_16","alias_value":"UIJNBKVRUJKAXU36","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"pith_short_8","alias_value":"UIJNBKVR","created_at":"2026-07-05T02:28:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:UIJNBKVRUJKAXU36XK4NMI2JGW","target":"record","payload":{"canonical_record":{"source":{"id":"2104.01394","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-03T13:01:19Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"fe8e59a889eb098c2f18b25960967d8f0006e3b6665fcb9814bce094ba5f1e73","abstract_canon_sha256":"9d0b50a2d77a77c2a72f54230378bc2476837225b18c09bf30e9bd91a9fbe3bd"},"schema_version":"1.0"},"canonical_sha256":"a212d0aab1a2540bd37ebab8d62349359764eb8fbcf71611e43b773f8f40a4e3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:28:59.557903Z","signature_b64":"jG2FgEc4fPtWrNvpLYLcWHl3yGeYznvbszdz9VGqUBcTAtE/OyOoqQL11CTvTRMSNKYhqOJblN/v2wercMQxBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a212d0aab1a2540bd37ebab8d62349359764eb8fbcf71611e43b773f8f40a4e3","last_reissued_at":"2026-07-05T02:28:59.557492Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:28:59.557492Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.01394","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:28:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0g3/fK/Lwj8KvQNAvDtJM7EE338/GbDKi2Vkv15QCuDyNtxhP7IlHeBNIlfNFLtt710jnWYrRB2xDu+aBdW+Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T19:31:00.667190Z"},"content_sha256":"9309a4c9c0c84394a96e08ab5eb58d2e258ed876ad0dfcd7597c2eb3a4356c50","schema_version":"1.0","event_id":"sha256:9309a4c9c0c84394a96e08ab5eb58d2e258ed876ad0dfcd7597c2eb3a4356c50"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:UIJNBKVRUJKAXU36XK4NMI2JGW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MMBERT: Multimodal BERT Pretraining for Improved Medical VQA","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.CV","authors_text":"Adithi Devi, CV Jawahar, Minesh Mathew, U Deva Priyakumar, Viraj Bagal, Yash Khare","submitted_at":"2021-04-03T13:01:19Z","abstract_excerpt":"Images in the medical domain are fundamentally different from the general domain images. Consequently, it is infeasible to directly employ general domain Visual Question Answering (VQA) models for the medical domain. Additionally, medical images annotation is a costly and time-consuming process. To overcome these limitations, we propose a solution inspired by self-supervised pretraining of Transformer-style architectures for NLP, Vision and Language tasks. Our method involves learning richer medical image and text semantic representations using Masked Language Modeling (MLM) with image feature"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.01394","kind":"arxiv","version":1},"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/2104.01394/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":"2026-07-05T02:28:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XHNAchOwzgOd1QbFpHDW1BT1eVQ2QvwBQheauSvxqpkpAsRJSaDYDQw72L3aJBS0U7lISf0tNlPelOI9PsrnAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T19:31:00.667583Z"},"content_sha256":"5da4ae801613b98f1b426065657113a9680446a048daffc10ceefa2814a9cb42","schema_version":"1.0","event_id":"sha256:5da4ae801613b98f1b426065657113a9680446a048daffc10ceefa2814a9cb42"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UIJNBKVRUJKAXU36XK4NMI2JGW/bundle.json","state_url":"https://pith.science/pith/UIJNBKVRUJKAXU36XK4NMI2JGW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UIJNBKVRUJKAXU36XK4NMI2JGW/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":"2026-07-24T19:31:00Z","links":{"resolver":"https://pith.science/pith/UIJNBKVRUJKAXU36XK4NMI2JGW","bundle":"https://pith.science/pith/UIJNBKVRUJKAXU36XK4NMI2JGW/bundle.json","state":"https://pith.science/pith/UIJNBKVRUJKAXU36XK4NMI2JGW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UIJNBKVRUJKAXU36XK4NMI2JGW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:UIJNBKVRUJKAXU36XK4NMI2JGW","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":"9d0b50a2d77a77c2a72f54230378bc2476837225b18c09bf30e9bd91a9fbe3bd","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-03T13:01:19Z","title_canon_sha256":"fe8e59a889eb098c2f18b25960967d8f0006e3b6665fcb9814bce094ba5f1e73"},"schema_version":"1.0","source":{"id":"2104.01394","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.01394","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"arxiv_version","alias_value":"2104.01394v1","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.01394","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"pith_short_12","alias_value":"UIJNBKVRUJKA","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"pith_short_16","alias_value":"UIJNBKVRUJKAXU36","created_at":"2026-07-05T02:28:59Z"},{"alias_kind":"pith_short_8","alias_value":"UIJNBKVR","created_at":"2026-07-05T02:28:59Z"}],"graph_snapshots":[{"event_id":"sha256:5da4ae801613b98f1b426065657113a9680446a048daffc10ceefa2814a9cb42","target":"graph","created_at":"2026-07-05T02:28:59Z","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/2104.01394/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Images in the medical domain are fundamentally different from the general domain images. Consequently, it is infeasible to directly employ general domain Visual Question Answering (VQA) models for the medical domain. Additionally, medical images annotation is a costly and time-consuming process. To overcome these limitations, we propose a solution inspired by self-supervised pretraining of Transformer-style architectures for NLP, Vision and Language tasks. Our method involves learning richer medical image and text semantic representations using Masked Language Modeling (MLM) with image feature","authors_text":"Adithi Devi, CV Jawahar, Minesh Mathew, U Deva Priyakumar, Viraj Bagal, Yash Khare","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-03T13:01:19Z","title":"MMBERT: Multimodal BERT Pretraining for Improved Medical VQA"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.01394","kind":"arxiv","version":1},"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":"sha256:9309a4c9c0c84394a96e08ab5eb58d2e258ed876ad0dfcd7597c2eb3a4356c50","target":"record","created_at":"2026-07-05T02:28:59Z","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":"9d0b50a2d77a77c2a72f54230378bc2476837225b18c09bf30e9bd91a9fbe3bd","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-03T13:01:19Z","title_canon_sha256":"fe8e59a889eb098c2f18b25960967d8f0006e3b6665fcb9814bce094ba5f1e73"},"schema_version":"1.0","source":{"id":"2104.01394","kind":"arxiv","version":1}},"canonical_sha256":"a212d0aab1a2540bd37ebab8d62349359764eb8fbcf71611e43b773f8f40a4e3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a212d0aab1a2540bd37ebab8d62349359764eb8fbcf71611e43b773f8f40a4e3","first_computed_at":"2026-07-05T02:28:59.557492Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:28:59.557492Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jG2FgEc4fPtWrNvpLYLcWHl3yGeYznvbszdz9VGqUBcTAtE/OyOoqQL11CTvTRMSNKYhqOJblN/v2wercMQxBA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:28:59.557903Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.01394","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9309a4c9c0c84394a96e08ab5eb58d2e258ed876ad0dfcd7597c2eb3a4356c50","sha256:5da4ae801613b98f1b426065657113a9680446a048daffc10ceefa2814a9cb42"],"state_sha256":"5415804a354839c68a3add34d06599902cbe88e0bb33c377cc69022e92fa3a77"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fj3pqSDkgODsZpCufjWaUS34jymywuy3Hy0qCq9cIsLEFjv2Fazj7QuFPMdbOcNhiuDH4Rl+ADTPWwSvx667CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-24T19:31:00.670093Z","bundle_sha256":"8b1f61db3d1009300ed3af1af436ce933c930bb8b3ed0efadbaef4c46b47c0de"}}