{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NVUMKNOZ3ETAGA5PUQD52P3775","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":"c39ad8acc3b7c1468f1267df21fbc4b9571ea6294e06e4893ba7ff50de309144","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-29T11:31:09Z","title_canon_sha256":"793173a82674814b9986d501b6f041e994062dd520c36bf34136c0be8332f799"},"schema_version":"1.0","source":{"id":"2407.00411","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.00411","created_at":"2026-07-05T10:03:43Z"},{"alias_kind":"arxiv_version","alias_value":"2407.00411v3","created_at":"2026-07-05T10:03:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.00411","created_at":"2026-07-05T10:03:43Z"},{"alias_kind":"pith_short_12","alias_value":"NVUMKNOZ3ETA","created_at":"2026-07-05T10:03:43Z"},{"alias_kind":"pith_short_16","alias_value":"NVUMKNOZ3ETAGA5P","created_at":"2026-07-05T10:03:43Z"},{"alias_kind":"pith_short_8","alias_value":"NVUMKNOZ","created_at":"2026-07-05T10:03:43Z"}],"graph_snapshots":[{"event_id":"sha256:da0c7b25e127577cadc9d94880889f3b3e43eca716020c8c091f8227386a774d","target":"graph","created_at":"2026-07-05T10:03:43Z","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/2407.00411/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Missing data is a prevalent issue that can significantly impair model performance and explainability. This paper briefly summarizes the development of the field of missing data with respect to Explainable Artificial Intelligence and experimentally investigates the effects of various imputation methods on SHAP (SHapley Additive exPlanations), a popular technique for explaining the output of complex machine learning models. Next, we compare different imputation strategies and assess their impact on feature importance and interaction as determined by Shapley values. Moreover, we also theoreticall","authors_text":"Hugo L. Hammer, Luis M. Lopez-Ramos, Michael A. Riegler, Pal Halvorsen, Thu Nguyen, Tuan L. Vo","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-29T11:31:09Z","title":"Explainability of Machine Learning Models under Missing Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.00411","kind":"arxiv","version":3},"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":"sha256:23d093ba8fe10f7da63da6ec4574e303d1f92287248983a1cbfae53b8a8f8482","target":"record","created_at":"2026-07-05T10:03:43Z","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":"c39ad8acc3b7c1468f1267df21fbc4b9571ea6294e06e4893ba7ff50de309144","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-29T11:31:09Z","title_canon_sha256":"793173a82674814b9986d501b6f041e994062dd520c36bf34136c0be8332f799"},"schema_version":"1.0","source":{"id":"2407.00411","kind":"arxiv","version":3}},"canonical_sha256":"6d68c535d9d9260303afa407dd3f7fff58a5ddf0b264dfdcef6a7dc525b8acb5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6d68c535d9d9260303afa407dd3f7fff58a5ddf0b264dfdcef6a7dc525b8acb5","first_computed_at":"2026-07-05T10:03:43.861610Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:03:43.861610Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9i4J80kRgjt5cr0QCsxsz8ldZmG8EX08QBZd/blrHyoeJemifHHkj+CGNdfqof3WDMhF+UEudPHeSNmRGeoQCg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:03:43.862071Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.00411","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:23d093ba8fe10f7da63da6ec4574e303d1f92287248983a1cbfae53b8a8f8482","sha256:da0c7b25e127577cadc9d94880889f3b3e43eca716020c8c091f8227386a774d"],"state_sha256":"264279b151eb0e554b7209d14af2dba7dc85d96398023c4a126f392420a6e2fa"}