{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WMK76ISPDPKUWHUKEUWTQGRVQB","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":"e06c420874ca5ec11d8e242e4f5c22b45864bdbf663384e4a9f30afe5b119d2d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-29T14:11:02Z","title_canon_sha256":"0f84946cb2386a57668457a03b7ece7cc6bcc6673bc138850f8f7459ca2f93e2"},"schema_version":"1.0","source":{"id":"2506.23247","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.23247","created_at":"2026-07-05T11:29:18Z"},{"alias_kind":"arxiv_version","alias_value":"2506.23247v1","created_at":"2026-07-05T11:29:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.23247","created_at":"2026-07-05T11:29:18Z"},{"alias_kind":"pith_short_12","alias_value":"WMK76ISPDPKU","created_at":"2026-07-05T11:29:18Z"},{"alias_kind":"pith_short_16","alias_value":"WMK76ISPDPKUWHUK","created_at":"2026-07-05T11:29:18Z"},{"alias_kind":"pith_short_8","alias_value":"WMK76ISP","created_at":"2026-07-05T11:29:18Z"}],"graph_snapshots":[{"event_id":"sha256:657b74636c42a86351806a45f9ef8aa16698fcd7d52f4b77812700f72e8731c2","target":"graph","created_at":"2026-07-05T11:29:18Z","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/2506.23247/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning dominates image classification tasks, yet understanding how models arrive at predictions remains a challenge. Much research focuses on local explanations of individual predictions, such as saliency maps, which visualise the influence of specific pixels on a model's prediction. However, reviewing many of these explanations to identify recurring patterns is infeasible, while global methods often oversimplify and miss important local behaviours. To address this, we propose Segment Attribution Tables (SATs), a method for summarising local saliency explanations into (semi-)global insi","authors_text":"David Martens, James Hinns","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-29T14:11:02Z","title":"Aggregating Local Saliency Maps for Semi-Global Explainable Image Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.23247","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":"sha256:71ecb9fff6e62d56c49a873cdf9a23b1b114ed377a55399ebe76d0f5b8910cc5","target":"record","created_at":"2026-07-05T11:29:18Z","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":"e06c420874ca5ec11d8e242e4f5c22b45864bdbf663384e4a9f30afe5b119d2d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-29T14:11:02Z","title_canon_sha256":"0f84946cb2386a57668457a03b7ece7cc6bcc6673bc138850f8f7459ca2f93e2"},"schema_version":"1.0","source":{"id":"2506.23247","kind":"arxiv","version":1}},"canonical_sha256":"b315ff224f1bd54b1e8a252d381a35806225236122d119b8f31818a54f7df977","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b315ff224f1bd54b1e8a252d381a35806225236122d119b8f31818a54f7df977","first_computed_at":"2026-07-05T11:29:18.537939Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:29:18.537939Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LWcf+jsIibZNw/ftZbDGn8p7UaBPc9RPkj8E2+z0Ph2oXGYUe3+cBcufRepAzqI1d943PGQ+C3uKDOg/q7VqBg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:29:18.538494Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.23247","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:71ecb9fff6e62d56c49a873cdf9a23b1b114ed377a55399ebe76d0f5b8910cc5","sha256:657b74636c42a86351806a45f9ef8aa16698fcd7d52f4b77812700f72e8731c2"],"state_sha256":"25ed899ef240f59452c265f593fc26914199979551ba6718b8cf7206e613a6d1"}