{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:YIZRZX5C4L3EAXTUC2DMLBKHW7","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":"5af729550d62d3b464ca72616aece2be6d13c442202d7c297c4978bbd05c7e81","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-05-20T13:36:41Z","title_canon_sha256":"be483c87d2c04f45be70ba0af2d71f7866482b8700d021a9ac5be58d4932c516"},"schema_version":"1.0","source":{"id":"2105.09740","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.09740","created_at":"2026-07-05T02:41:56Z"},{"alias_kind":"arxiv_version","alias_value":"2105.09740v1","created_at":"2026-07-05T02:41:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.09740","created_at":"2026-07-05T02:41:56Z"},{"alias_kind":"pith_short_12","alias_value":"YIZRZX5C4L3E","created_at":"2026-07-05T02:41:56Z"},{"alias_kind":"pith_short_16","alias_value":"YIZRZX5C4L3EAXTU","created_at":"2026-07-05T02:41:56Z"},{"alias_kind":"pith_short_8","alias_value":"YIZRZX5C","created_at":"2026-07-05T02:41:56Z"}],"graph_snapshots":[{"event_id":"sha256:d912069826238ce2fd18863ab3522baf7259e834950afa8d4971ef0d5b9e129a","target":"graph","created_at":"2026-07-05T02:41:56Z","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/2105.09740/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Explainable AI has attracted much research attention in recent years with feature attribution algorithms, which compute \"feature importance\" in predictions, becoming increasingly popular. However, there is little analysis of the validity of these algorithms as there is no \"ground truth\" in the existing datasets to validate their correctness. In this work, we develop a method to quantitatively evaluate the correctness of XAI algorithms by creating datasets with known explanation ground truth. To this end, we focus on the binary classification problems. String datasets are constructed using form","authors_text":"Orcun Yalcin, Siyuan Liu, Xiuyi Fan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-05-20T13:36:41Z","title":"Evaluating the Correctness of Explainable AI Algorithms for Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.09740","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":"sha256:71c69b507a4cda0f6085ad7b03b3390bd6b1845c82c93a7f8454631efe0e13a1","target":"record","created_at":"2026-07-05T02:41:56Z","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":"5af729550d62d3b464ca72616aece2be6d13c442202d7c297c4978bbd05c7e81","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-05-20T13:36:41Z","title_canon_sha256":"be483c87d2c04f45be70ba0af2d71f7866482b8700d021a9ac5be58d4932c516"},"schema_version":"1.0","source":{"id":"2105.09740","kind":"arxiv","version":1}},"canonical_sha256":"c2331cdfa2e2f6405e741686c58547b7d093cbf14d4b44e60bcaa90bbc6a5e85","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c2331cdfa2e2f6405e741686c58547b7d093cbf14d4b44e60bcaa90bbc6a5e85","first_computed_at":"2026-07-05T02:41:56.786737Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:41:56.786737Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"culC5Hb1Ljm422OshGlZHmPVUlAXOZzB1JULDP0OiUzAQg3sHg8eAjUB0dQmfbfNhaSaceBoZ0xwh0IDuU8WDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:41:56.787151Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.09740","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:71c69b507a4cda0f6085ad7b03b3390bd6b1845c82c93a7f8454631efe0e13a1","sha256:d912069826238ce2fd18863ab3522baf7259e834950afa8d4971ef0d5b9e129a"],"state_sha256":"7becf16e6fbb4217dadb400f873a3b0f6503d3e48429502ef813f0523ef14fae"}