{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:O3FBQO5JKY22TVLZY7747ZB6AC","short_pith_number":"pith:O3FBQO5J","canonical_record":{"source":{"id":"2608.12903","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-08-13T07:39:46Z","cross_cats_sorted":[],"title_canon_sha256":"40d710adc7bf66470847264c0b89f128f3c478956787bcfe93243d85ec7e5a9e","abstract_canon_sha256":"79469a000d081fb2acc75c6c284b637fb169203038c2a9b00745b724668acc5b"},"schema_version":"1.0"},"canonical_sha256":"76ca183ba95635a9d579c7ffcfe43e00b061954c465edc2503d87e6a2eb1407d","source":{"kind":"arxiv","id":"2608.12903","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.12903","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"arxiv_version","alias_value":"2608.12903v1","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.12903","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"pith_short_12","alias_value":"O3FBQO5JKY22","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"pith_short_16","alias_value":"O3FBQO5JKY22TVLZ","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"pith_short_8","alias_value":"O3FBQO5J","created_at":"2026-08-14T00:58:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:O3FBQO5JKY22TVLZY7747ZB6AC","target":"record","payload":{"canonical_record":{"source":{"id":"2608.12903","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-08-13T07:39:46Z","cross_cats_sorted":[],"title_canon_sha256":"40d710adc7bf66470847264c0b89f128f3c478956787bcfe93243d85ec7e5a9e","abstract_canon_sha256":"79469a000d081fb2acc75c6c284b637fb169203038c2a9b00745b724668acc5b"},"schema_version":"1.0"},"canonical_sha256":"76ca183ba95635a9d579c7ffcfe43e00b061954c465edc2503d87e6a2eb1407d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-14T00:58:44.978434Z","signature_b64":"WwmQ/X/nCF1+sZq3cAcFWY6XzSypUMZBjB6gwVbtG6jd+UoLulsk5H+oroNRh38rt4r83QR/teN+3+Epa/9eDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"76ca183ba95635a9d579c7ffcfe43e00b061954c465edc2503d87e6a2eb1407d","last_reissued_at":"2026-08-14T00:58:44.975811Z","signature_status":"signed_v1","first_computed_at":"2026-08-14T00:58:44.975811Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.12903","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":"2026-08-14T00:58:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JNhVMhvmEG78E+JWtTp0RwNKV+MdXk/UK4sHQis6vHjNj2tYJ+Cc7lhjpHof9p7EFNmxLzmE1x3+vzbE6vQKCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T07:02:05.588938Z"},"content_sha256":"0d0defdd39a5c99cd0d64590ff0a651b13e8daed562bb41b075b4db39768fbad","schema_version":"1.0","event_id":"sha256:0d0defdd39a5c99cd0d64590ff0a651b13e8daed562bb41b075b4db39768fbad"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:O3FBQO5JKY22TVLZY7747ZB6AC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptive $k$ Nearest Neighbors Classifier via Granular Ball Computing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Guoyin Wang, Hongxuan He, Lifeng Shen, Shuyin Xia, Xiaoyu Lian, Xinbo Gao","submitted_at":"2026-08-13T07:39:46Z","abstract_excerpt":"The $k$-Nearest Neighbor~(KNN) algorithm is widely used across various tasks. The selection of the $k$ value is a key issue because it significantly impacts performance. In this paper, an adaptive and efficient KNN approach via granular-ball computing is proposed. The method consists of two stages. \\textcolor{black}{In the training stage, the dataset is first coarsely partitioned to reduce the complexity of data distributions within a granular ball, and then the Fisher criterion is introduced to control ball splitting and stopping, yielding a multi-granularity granular ball representation. In "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.12903","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/2608.12903/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":"2026-08-14T00:58:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eEC6GA92gLpEgTKB/QL6d9C5eUmAIdC+2cbFH4ZE/f8MRbYmfjrwQ3ahE2SpZqIr7gZ8AjhdgloekeXnjHd6Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T07:02:05.589455Z"},"content_sha256":"8f76e2cf841cc31ea62f97aa0b6a24cc4500f4341859c5bd6072836ab710edfb","schema_version":"1.0","event_id":"sha256:8f76e2cf841cc31ea62f97aa0b6a24cc4500f4341859c5bd6072836ab710edfb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/O3FBQO5JKY22TVLZY7747ZB6AC/bundle.json","state_url":"https://pith.science/pith/O3FBQO5JKY22TVLZY7747ZB6AC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/O3FBQO5JKY22TVLZY7747ZB6AC/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":"2026-08-21T07:02:05Z","links":{"resolver":"https://pith.science/pith/O3FBQO5JKY22TVLZY7747ZB6AC","bundle":"https://pith.science/pith/O3FBQO5JKY22TVLZY7747ZB6AC/bundle.json","state":"https://pith.science/pith/O3FBQO5JKY22TVLZY7747ZB6AC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/O3FBQO5JKY22TVLZY7747ZB6AC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:O3FBQO5JKY22TVLZY7747ZB6AC","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":"79469a000d081fb2acc75c6c284b637fb169203038c2a9b00745b724668acc5b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-08-13T07:39:46Z","title_canon_sha256":"40d710adc7bf66470847264c0b89f128f3c478956787bcfe93243d85ec7e5a9e"},"schema_version":"1.0","source":{"id":"2608.12903","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.12903","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"arxiv_version","alias_value":"2608.12903v1","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.12903","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"pith_short_12","alias_value":"O3FBQO5JKY22","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"pith_short_16","alias_value":"O3FBQO5JKY22TVLZ","created_at":"2026-08-14T00:58:44Z"},{"alias_kind":"pith_short_8","alias_value":"O3FBQO5J","created_at":"2026-08-14T00:58:44Z"}],"graph_snapshots":[{"event_id":"sha256:8f76e2cf841cc31ea62f97aa0b6a24cc4500f4341859c5bd6072836ab710edfb","target":"graph","created_at":"2026-08-14T00:58:44Z","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/2608.12903/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The $k$-Nearest Neighbor~(KNN) algorithm is widely used across various tasks. The selection of the $k$ value is a key issue because it significantly impacts performance. In this paper, an adaptive and efficient KNN approach via granular-ball computing is proposed. The method consists of two stages. \\textcolor{black}{In the training stage, the dataset is first coarsely partitioned to reduce the complexity of data distributions within a granular ball, and then the Fisher criterion is introduced to control ball splitting and stopping, yielding a multi-granularity granular ball representation. In ","authors_text":"Guoyin Wang, Hongxuan He, Lifeng Shen, Shuyin Xia, Xiaoyu Lian, Xinbo Gao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-08-13T07:39:46Z","title":"Adaptive $k$ Nearest Neighbors Classifier via Granular Ball Computing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.12903","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":"sha256:0d0defdd39a5c99cd0d64590ff0a651b13e8daed562bb41b075b4db39768fbad","target":"record","created_at":"2026-08-14T00:58:44Z","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":"79469a000d081fb2acc75c6c284b637fb169203038c2a9b00745b724668acc5b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-08-13T07:39:46Z","title_canon_sha256":"40d710adc7bf66470847264c0b89f128f3c478956787bcfe93243d85ec7e5a9e"},"schema_version":"1.0","source":{"id":"2608.12903","kind":"arxiv","version":1}},"canonical_sha256":"76ca183ba95635a9d579c7ffcfe43e00b061954c465edc2503d87e6a2eb1407d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"76ca183ba95635a9d579c7ffcfe43e00b061954c465edc2503d87e6a2eb1407d","first_computed_at":"2026-08-14T00:58:44.975811Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-14T00:58:44.975811Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WwmQ/X/nCF1+sZq3cAcFWY6XzSypUMZBjB6gwVbtG6jd+UoLulsk5H+oroNRh38rt4r83QR/teN+3+Epa/9eDQ==","signature_status":"signed_v1","signed_at":"2026-08-14T00:58:44.978434Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.12903","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0d0defdd39a5c99cd0d64590ff0a651b13e8daed562bb41b075b4db39768fbad","sha256:8f76e2cf841cc31ea62f97aa0b6a24cc4500f4341859c5bd6072836ab710edfb"],"state_sha256":"d12749fff9c589576e2ba40d58ef7ea31d8bb2a2a3d495af21f08999ea677c89"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3GAIIlg1VIpkGYVsKceNrEDr1LafcsDZ+/Zo+DF8iJmTOak8sOxhYwnAIZuz/3bwJqOOTwd87qJJjMub7oh/Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T07:02:05.594608Z","bundle_sha256":"e6307eb8e3b68201bd41f051e0dd771ec01762a4b4d8a8fc2c035227d75b7509"}}