{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XJDHT6EW5ACKE4ZSJ335ABHOGP","short_pith_number":"pith:XJDHT6EW","canonical_record":{"source":{"id":"2505.11262","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-05-16T13:54:29Z","cross_cats_sorted":[],"title_canon_sha256":"f8ff5c3a4fcfe9a86bd805f6a9c25eb22c4148612e801708b78d1f6df04dbc74","abstract_canon_sha256":"46e1430d655d0fb9146ca09a1acbebb15363e94581340aa91d5c83b2a9654f9c"},"schema_version":"1.0"},"canonical_sha256":"ba4679f896e804a273324ef7d004ee33f86a4925b8cd07a8cf2283d4933cee4e","source":{"kind":"arxiv","id":"2505.11262","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11262","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11262v1","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11262","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"pith_short_12","alias_value":"XJDHT6EW5ACK","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"pith_short_16","alias_value":"XJDHT6EW5ACKE4ZS","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"pith_short_8","alias_value":"XJDHT6EW","created_at":"2026-07-05T11:04:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XJDHT6EW5ACKE4ZSJ335ABHOGP","target":"record","payload":{"canonical_record":{"source":{"id":"2505.11262","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-05-16T13:54:29Z","cross_cats_sorted":[],"title_canon_sha256":"f8ff5c3a4fcfe9a86bd805f6a9c25eb22c4148612e801708b78d1f6df04dbc74","abstract_canon_sha256":"46e1430d655d0fb9146ca09a1acbebb15363e94581340aa91d5c83b2a9654f9c"},"schema_version":"1.0"},"canonical_sha256":"ba4679f896e804a273324ef7d004ee33f86a4925b8cd07a8cf2283d4933cee4e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:04:13.557766Z","signature_b64":"WIvWv7Qd00m24zyoFvnLbW3Cbt3eOOehnFSkYZov8s85+DCgm5IqGWvuDrP81vkU8Lshl/AmfRNE3wPTynXFBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba4679f896e804a273324ef7d004ee33f86a4925b8cd07a8cf2283d4933cee4e","last_reissued_at":"2026-07-05T11:04:13.557274Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:04:13.557274Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.11262","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":"2026-07-05T11:04:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ufsw/3+PBOVd9+tvmisHNCkY5x73zyjNXscx5SkLqAjsY/hV524gHS/qzv0YmKSam6xlc465USpDQNaUt/KdAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T11:55:15.084611Z"},"content_sha256":"d76e7a203771c8f3844c69ff70672abd66821942091928e067b9456b8972b342","schema_version":"1.0","event_id":"sha256:d76e7a203771c8f3844c69ff70672abd66821942091928e067b9456b8972b342"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XJDHT6EW5ACKE4ZSJ335ABHOGP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Step towards Interpretable Multimodal AI Models with MultiFIX","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Mafalda Malafaia, Peter A. N. Bosman, Tanja Alderliesten, Thalea Schlender","submitted_at":"2025-05-16T13:54:29Z","abstract_excerpt":"Real-world problems are often dependent on multiple data modalities, making multimodal fusion essential for leveraging diverse information sources. In high-stakes domains, such as in healthcare, understanding how each modality contributes to the prediction is critical to ensure trustworthy and interpretable AI models. We present MultiFIX, an interpretability-driven multimodal data fusion pipeline that explicitly engineers distinct features from different modalities and combines them to make the final prediction. Initially, only deep learning components are used to train a model from data. The "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11262","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/2505.11262/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":"2026-07-05T11:04:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XRk58e+1HWwtljjGlZRWJNWsKTLBP84n2//y7Hd4G0Qt9Sv3eMIeU5ex3XjEgPTHecBKbhrwuT1abi8wfZjpAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T11:55:15.085103Z"},"content_sha256":"ffbc6d6b4374209b5ddc75402d8a2c4f83cad79cea666641f639a63c2048fabd","schema_version":"1.0","event_id":"sha256:ffbc6d6b4374209b5ddc75402d8a2c4f83cad79cea666641f639a63c2048fabd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XJDHT6EW5ACKE4ZSJ335ABHOGP/bundle.json","state_url":"https://pith.science/pith/XJDHT6EW5ACKE4ZSJ335ABHOGP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XJDHT6EW5ACKE4ZSJ335ABHOGP/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":"2026-08-18T11:55:15Z","links":{"resolver":"https://pith.science/pith/XJDHT6EW5ACKE4ZSJ335ABHOGP","bundle":"https://pith.science/pith/XJDHT6EW5ACKE4ZSJ335ABHOGP/bundle.json","state":"https://pith.science/pith/XJDHT6EW5ACKE4ZSJ335ABHOGP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XJDHT6EW5ACKE4ZSJ335ABHOGP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XJDHT6EW5ACKE4ZSJ335ABHOGP","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":"46e1430d655d0fb9146ca09a1acbebb15363e94581340aa91d5c83b2a9654f9c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-05-16T13:54:29Z","title_canon_sha256":"f8ff5c3a4fcfe9a86bd805f6a9c25eb22c4148612e801708b78d1f6df04dbc74"},"schema_version":"1.0","source":{"id":"2505.11262","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.11262","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"arxiv_version","alias_value":"2505.11262v1","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.11262","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"pith_short_12","alias_value":"XJDHT6EW5ACK","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"pith_short_16","alias_value":"XJDHT6EW5ACKE4ZS","created_at":"2026-07-05T11:04:13Z"},{"alias_kind":"pith_short_8","alias_value":"XJDHT6EW","created_at":"2026-07-05T11:04:13Z"}],"graph_snapshots":[{"event_id":"sha256:ffbc6d6b4374209b5ddc75402d8a2c4f83cad79cea666641f639a63c2048fabd","target":"graph","created_at":"2026-07-05T11:04:13Z","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/2505.11262/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Real-world problems are often dependent on multiple data modalities, making multimodal fusion essential for leveraging diverse information sources. In high-stakes domains, such as in healthcare, understanding how each modality contributes to the prediction is critical to ensure trustworthy and interpretable AI models. We present MultiFIX, an interpretability-driven multimodal data fusion pipeline that explicitly engineers distinct features from different modalities and combines them to make the final prediction. Initially, only deep learning components are used to train a model from data. The ","authors_text":"Mafalda Malafaia, Peter A. N. Bosman, Tanja Alderliesten, Thalea Schlender","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-05-16T13:54:29Z","title":"A Step towards Interpretable Multimodal AI Models with MultiFIX"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.11262","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:d76e7a203771c8f3844c69ff70672abd66821942091928e067b9456b8972b342","target":"record","created_at":"2026-07-05T11:04:13Z","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":"46e1430d655d0fb9146ca09a1acbebb15363e94581340aa91d5c83b2a9654f9c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.NE","submitted_at":"2025-05-16T13:54:29Z","title_canon_sha256":"f8ff5c3a4fcfe9a86bd805f6a9c25eb22c4148612e801708b78d1f6df04dbc74"},"schema_version":"1.0","source":{"id":"2505.11262","kind":"arxiv","version":1}},"canonical_sha256":"ba4679f896e804a273324ef7d004ee33f86a4925b8cd07a8cf2283d4933cee4e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ba4679f896e804a273324ef7d004ee33f86a4925b8cd07a8cf2283d4933cee4e","first_computed_at":"2026-07-05T11:04:13.557274Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:04:13.557274Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WIvWv7Qd00m24zyoFvnLbW3Cbt3eOOehnFSkYZov8s85+DCgm5IqGWvuDrP81vkU8Lshl/AmfRNE3wPTynXFBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:04:13.557766Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.11262","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d76e7a203771c8f3844c69ff70672abd66821942091928e067b9456b8972b342","sha256:ffbc6d6b4374209b5ddc75402d8a2c4f83cad79cea666641f639a63c2048fabd"],"state_sha256":"2604a5104a95e4c98fc61e3dbc3210c1e2be89ca71d133d85c0994db2eba3cba"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pf5bNOddswhAohcHfimHgSZBxMg0yQ15JQCV0hL2nVGFVTE3NJoJSKJNQncLVP+h2HN+ae43qa60WRAgVuf3DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T11:55:15.088708Z","bundle_sha256":"d9dcae557f539438c1104f59d4f98dd97bf6c780393b3fa4e38911bb0eae7588"}}