{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5SVA4UFKF63IUXQPES7LG3GNRL","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":"e74d93003168aa836ee459e27b76ef9d092b0496d55709a9c1d61ea016ac34cc","cross_cats_sorted":["cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-25T19:40:56Z","title_canon_sha256":"4d5d727f06144c528e3c3b35d0f8b4092ce03e98379bce22101340f02d2f2304"},"schema_version":"1.0","source":{"id":"2308.13651","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.13651","created_at":"2026-07-05T08:59:23Z"},{"alias_kind":"arxiv_version","alias_value":"2308.13651v5","created_at":"2026-07-05T08:59:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.13651","created_at":"2026-07-05T08:59:23Z"},{"alias_kind":"pith_short_12","alias_value":"5SVA4UFKF63I","created_at":"2026-07-05T08:59:23Z"},{"alias_kind":"pith_short_16","alias_value":"5SVA4UFKF63IUXQP","created_at":"2026-07-05T08:59:23Z"},{"alias_kind":"pith_short_8","alias_value":"5SVA4UFK","created_at":"2026-07-05T08:59:23Z"}],"graph_snapshots":[{"event_id":"sha256:32083bcc28766de8ffc9b156a8512c36c046da68f8e41a72877983033ff05f88","target":"graph","created_at":"2026-07-05T08:59:23Z","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/2308.13651/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Nearest neighbors (NN) are traditionally used to compute final decisions, e.g., in Support Vector Machines or k-NN classifiers, and to provide users with explanations for the model's decision. In this paper, we show a novel utility of nearest neighbors: To improve predictions of a frozen, pretrained image classifier C. We leverage an image comparator S that (1) compares the input image with NN images from the top-K most probable classes given by C; and (2) uses scores from S to weight the confidence scores of C to refine predictions. Our method consistently improves fine-grained image classifi","authors_text":"Anh Totti Nguyen, Giang (Dexter) Nguyen, Mohammad Reza Taesiri, Valerie Chen","cross_cats":["cs.HC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-25T19:40:56Z","title":"PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.13651","kind":"arxiv","version":5},"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":"sha256:8e70e68d97a12816071d5be0b914a3d6240b908850860182fa44f85f913cf92a","target":"record","created_at":"2026-07-05T08:59:23Z","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":"e74d93003168aa836ee459e27b76ef9d092b0496d55709a9c1d61ea016ac34cc","cross_cats_sorted":["cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-25T19:40:56Z","title_canon_sha256":"4d5d727f06144c528e3c3b35d0f8b4092ce03e98379bce22101340f02d2f2304"},"schema_version":"1.0","source":{"id":"2308.13651","kind":"arxiv","version":5}},"canonical_sha256":"ecaa0e50aa2fb68a5e0f24beb36ccd8ac2e1a5550e29120135a013e6d7fbaf5c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ecaa0e50aa2fb68a5e0f24beb36ccd8ac2e1a5550e29120135a013e6d7fbaf5c","first_computed_at":"2026-07-05T08:59:23.932417Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:59:23.932417Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hyTseKiLyIxbJrqmzWzzBWz6nRSh3zjBeYAhP1BgLDVch3gRnSI+DPKMWtnMls9y/v7AAssNikMFCeuF4FfkDg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:59:23.932872Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.13651","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8e70e68d97a12816071d5be0b914a3d6240b908850860182fa44f85f913cf92a","sha256:32083bcc28766de8ffc9b156a8512c36c046da68f8e41a72877983033ff05f88"],"state_sha256":"cfb381e7f38a43d5401bff5b1201a50adfcc9d48768273e67adfafe01bed0949"}