{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RRVSBEKBBLDYP42ZAFI2BQWS7G","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":"16d2ecccf805765627467c7c3a76508affb8f808e997c0ea21f493f50a375b7c","cross_cats_sorted":["cs.AI","cs.NA","cs.NE","math.NA"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-15T03:24:07Z","title_canon_sha256":"748f56ce6c4095afb0c991849220426abcceca6e857f31eaa2ca9174f0d9ab54"},"schema_version":"1.0","source":{"id":"2408.07906","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.07906","created_at":"2026-07-05T08:55:41Z"},{"alias_kind":"arxiv_version","alias_value":"2408.07906v1","created_at":"2026-07-05T08:55:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.07906","created_at":"2026-07-05T08:55:41Z"},{"alias_kind":"pith_short_12","alias_value":"RRVSBEKBBLDY","created_at":"2026-07-05T08:55:41Z"},{"alias_kind":"pith_short_16","alias_value":"RRVSBEKBBLDYP42Z","created_at":"2026-07-05T08:55:41Z"},{"alias_kind":"pith_short_8","alias_value":"RRVSBEKB","created_at":"2026-07-05T08:55:41Z"}],"graph_snapshots":[{"event_id":"sha256:2d47668eef004f4f66c538ff66a3d4a42ef1f3f6e6bc3c910d13779de58354c2","target":"graph","created_at":"2026-07-05T08:55:41Z","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/2408.07906/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we compare the performance of Kolmogorov-Arnold Networks (KAN) and Multi-Layer Perceptron (MLP) networks on irregular or noisy functions. We control the number of parameters and the size of the training samples to ensure a fair comparison. For clarity, we categorize the functions into six types: regular functions, continuous functions with local non-differentiable points, functions with jump discontinuities, functions with singularities, functions with coherent oscillations, and noisy functions. Our experimental results indicate that KAN does not always perform best. For some ty","authors_text":"Chen Zeng, Haoran Shen, Jiahui Wang, Qiao Wang","cross_cats":["cs.AI","cs.NA","cs.NE","math.NA"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-15T03:24:07Z","title":"KAN versus MLP on Irregular or Noisy Functions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.07906","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:dc1fcbd24d08919930b88d0fdef21b1fdde695f70ac9fd9cbde913817f3bcfcd","target":"record","created_at":"2026-07-05T08:55:41Z","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":"16d2ecccf805765627467c7c3a76508affb8f808e997c0ea21f493f50a375b7c","cross_cats_sorted":["cs.AI","cs.NA","cs.NE","math.NA"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-15T03:24:07Z","title_canon_sha256":"748f56ce6c4095afb0c991849220426abcceca6e857f31eaa2ca9174f0d9ab54"},"schema_version":"1.0","source":{"id":"2408.07906","kind":"arxiv","version":1}},"canonical_sha256":"8c6b2091410ac787f3590151a0c2d2f985a601ec18707756e8b31054ec99568d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8c6b2091410ac787f3590151a0c2d2f985a601ec18707756e8b31054ec99568d","first_computed_at":"2026-07-05T08:55:41.783078Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:55:41.783078Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z8g9/u8VVTKVrb+nV71SR7jv1IiQ4veFTX3D7Nfot1ii1m1PMWp5rnlMttuoIl5FKBBIstBNtnGZu/sgh32OCA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:55:41.783556Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.07906","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dc1fcbd24d08919930b88d0fdef21b1fdde695f70ac9fd9cbde913817f3bcfcd","sha256:2d47668eef004f4f66c538ff66a3d4a42ef1f3f6e6bc3c910d13779de58354c2"],"state_sha256":"c39d45c2fc848c1c7f30aa34e05ad5f91b50d826ad951ae92968001d5c5bfade"}