{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:7QFXT4CJKNL6EJ5LXTUNCZO5HC","short_pith_number":"pith:7QFXT4CJ","schema_version":"1.0","canonical_sha256":"fc0b79f0495357e227abbce8d165dd389f42fbd471e5444af443b111a19380fe","source":{"kind":"arxiv","id":"2605.29039","version":1},"attestation_state":"computed","paper":{"title":"Kolmogorov--Arnold Networks as Implicit Regularizers: Noise Robustness and Interpretability for Stellar Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.IM","authors_text":"Kristian Sestak","submitted_at":"2026-05-27T19:38:46Z","abstract_excerpt":"This paper tests whether Kolmogorov--Arnold Networks (KAN 2.0) are genuinely more noise-robust than Multi-Layer Perceptrons (MLP) and XGBoost for stellar classification (star/galaxy/quasar, 100,000 SDSS DR17 objects). A naive comparison suggests so: KAN retains +9 percentage points over MLP at SNR=5. But equalizing baseline accuracy via weight decay eliminates the gap -- a properly regularized MLP matches KAN to within 1 p.p. at all SNR levels, both with and without spectroscopic redshift. The same holds on an independent DESI DR1 sample with different photometric bands. KAN's robustness thus "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.29039","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2026-05-27T19:38:46Z","cross_cats_sorted":[],"title_canon_sha256":"a1fb63a1abc59a4ce5a9918bcd952c9048cb69ef8dbe2a848de591ebff9d163a","abstract_canon_sha256":"780c2f60028b094e157f14501dfa8bf6f39cb643ec6100a8298104e5c6b97379"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T01:04:44.154543Z","signature_b64":"fF3Z77bLBu/Ob307yfP5UvrBhssNte+B6+ZUXTamj9sBjqa3zNaJBpiPrhDgxGW3o97dKXyju2/yXiaJvSwoDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc0b79f0495357e227abbce8d165dd389f42fbd471e5444af443b111a19380fe","last_reissued_at":"2026-05-29T01:04:44.154045Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T01:04:44.154045Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Kolmogorov--Arnold Networks as Implicit Regularizers: Noise Robustness and Interpretability for Stellar Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.IM","authors_text":"Kristian Sestak","submitted_at":"2026-05-27T19:38:46Z","abstract_excerpt":"This paper tests whether Kolmogorov--Arnold Networks (KAN 2.0) are genuinely more noise-robust than Multi-Layer Perceptrons (MLP) and XGBoost for stellar classification (star/galaxy/quasar, 100,000 SDSS DR17 objects). A naive comparison suggests so: KAN retains +9 percentage points over MLP at SNR=5. But equalizing baseline accuracy via weight decay eliminates the gap -- a properly regularized MLP matches KAN to within 1 p.p. at all SNR levels, both with and without spectroscopic redshift. The same holds on an independent DESI DR1 sample with different photometric bands. KAN's robustness thus "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29039","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/2605.29039/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.29039","created_at":"2026-05-29T01:04:44.154128+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.29039v1","created_at":"2026-05-29T01:04:44.154128+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29039","created_at":"2026-05-29T01:04:44.154128+00:00"},{"alias_kind":"pith_short_12","alias_value":"7QFXT4CJKNL6","created_at":"2026-05-29T01:04:44.154128+00:00"},{"alias_kind":"pith_short_16","alias_value":"7QFXT4CJKNL6EJ5L","created_at":"2026-05-29T01:04:44.154128+00:00"},{"alias_kind":"pith_short_8","alias_value":"7QFXT4CJ","created_at":"2026-05-29T01:04:44.154128+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7QFXT4CJKNL6EJ5LXTUNCZO5HC","json":"https://pith.science/pith/7QFXT4CJKNL6EJ5LXTUNCZO5HC.json","graph_json":"https://pith.science/api/pith-number/7QFXT4CJKNL6EJ5LXTUNCZO5HC/graph.json","events_json":"https://pith.science/api/pith-number/7QFXT4CJKNL6EJ5LXTUNCZO5HC/events.json","paper":"https://pith.science/paper/7QFXT4CJ"},"agent_actions":{"view_html":"https://pith.science/pith/7QFXT4CJKNL6EJ5LXTUNCZO5HC","download_json":"https://pith.science/pith/7QFXT4CJKNL6EJ5LXTUNCZO5HC.json","view_paper":"https://pith.science/paper/7QFXT4CJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.29039&json=true","fetch_graph":"https://pith.science/api/pith-number/7QFXT4CJKNL6EJ5LXTUNCZO5HC/graph.json","fetch_events":"https://pith.science/api/pith-number/7QFXT4CJKNL6EJ5LXTUNCZO5HC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7QFXT4CJKNL6EJ5LXTUNCZO5HC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7QFXT4CJKNL6EJ5LXTUNCZO5HC/action/storage_attestation","attest_author":"https://pith.science/pith/7QFXT4CJKNL6EJ5LXTUNCZO5HC/action/author_attestation","sign_citation":"https://pith.science/pith/7QFXT4CJKNL6EJ5LXTUNCZO5HC/action/citation_signature","submit_replication":"https://pith.science/pith/7QFXT4CJKNL6EJ5LXTUNCZO5HC/action/replication_record"}},"created_at":"2026-05-29T01:04:44.154128+00:00","updated_at":"2026-05-29T01:04:44.154128+00:00"}