{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:E3BYVNFHILDKP5BGOWQLHA7JSS","short_pith_number":"pith:E3BYVNFH","canonical_record":{"source":{"id":"2507.14121","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T17:50:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d875816c820946146d87a3eb23132331c0cd90705dc46e8bb677c6423b32160b","abstract_canon_sha256":"c2bf275fe66890daff1733eded2e4958b4b70c8f7d6e0a9abe280ed588492a12"},"schema_version":"1.0"},"canonical_sha256":"26c38ab4a742c6a7f42675a0b383e99491e4ff7e3121eed360eceedf72de131a","source":{"kind":"arxiv","id":"2507.14121","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.14121","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"arxiv_version","alias_value":"2507.14121v1","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.14121","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"pith_short_12","alias_value":"E3BYVNFHILDK","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"pith_short_16","alias_value":"E3BYVNFHILDKP5BG","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"pith_short_8","alias_value":"E3BYVNFH","created_at":"2026-07-05T11:39:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:E3BYVNFHILDKP5BGOWQLHA7JSS","target":"record","payload":{"canonical_record":{"source":{"id":"2507.14121","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T17:50:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d875816c820946146d87a3eb23132331c0cd90705dc46e8bb677c6423b32160b","abstract_canon_sha256":"c2bf275fe66890daff1733eded2e4958b4b70c8f7d6e0a9abe280ed588492a12"},"schema_version":"1.0"},"canonical_sha256":"26c38ab4a742c6a7f42675a0b383e99491e4ff7e3121eed360eceedf72de131a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:39:29.026918Z","signature_b64":"iMudp50klSAOlJDJivkvIUN9yn1olgl7GM+nKtZXCSUjsmKHwm0cxd38S1tSeG4TBBDWzTuENHoyKffixRbxAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"26c38ab4a742c6a7f42675a0b383e99491e4ff7e3121eed360eceedf72de131a","last_reissued_at":"2026-07-05T11:39:29.026498Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:39:29.026498Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.14121","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":"2026-07-05T11:39:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PExYbHd91iuVQe5b87szxc9W7Mwa7+i/M2KyG30sIKVLOcU28RxbZE2sRX+pxIGdZIEH2prH8J4eSoOiIsP5Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:40:20.702510Z"},"content_sha256":"24e2b99aa77f8fb679e75f7b0d03bb7cde201c1efd6fa26002e343796d0549ff","schema_version":"1.0","event_id":"sha256:24e2b99aa77f8fb679e75f7b0d03bb7cde201c1efd6fa26002e343796d0549ff"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:E3BYVNFHILDKP5BGOWQLHA7JSS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Kolmogorov Arnold Networks (KANs) for Imbalanced Data -- An Empirical Perspective","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Pankaj Yadav, Vivek Vijay","submitted_at":"2025-07-18T17:50:51Z","abstract_excerpt":"Kolmogorov Arnold Networks (KANs) are recent architectural advancement in neural computation that offer a mathematically grounded alternative to standard neural networks. This study presents an empirical evaluation of KANs in context of class imbalanced classification, using ten benchmark datasets. We observe that KANs can inherently perform well on raw imbalanced data more effectively than Multi-Layer Perceptrons (MLPs) without any resampling strategy. However, conventional imbalance strategies fundamentally conflict with KANs mathematical structure as resampling and focal loss implementation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.14121","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/2507.14121/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":"2026-07-05T11:39:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fUWcL649AtqVHj7m2mueOeU3NDFIZAvclTVsGsPw+1PLAHhRyONzRvZXtjtUJqDbbLjzOnmgFdCALVqgOemdAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:40:20.703052Z"},"content_sha256":"5b41f8daea9ba83596357ae76fa60713bb680a1da244d1c73c8692bd19ae19b8","schema_version":"1.0","event_id":"sha256:5b41f8daea9ba83596357ae76fa60713bb680a1da244d1c73c8692bd19ae19b8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E3BYVNFHILDKP5BGOWQLHA7JSS/bundle.json","state_url":"https://pith.science/pith/E3BYVNFHILDKP5BGOWQLHA7JSS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E3BYVNFHILDKP5BGOWQLHA7JSS/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":"2026-08-08T13:40:20Z","links":{"resolver":"https://pith.science/pith/E3BYVNFHILDKP5BGOWQLHA7JSS","bundle":"https://pith.science/pith/E3BYVNFHILDKP5BGOWQLHA7JSS/bundle.json","state":"https://pith.science/pith/E3BYVNFHILDKP5BGOWQLHA7JSS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E3BYVNFHILDKP5BGOWQLHA7JSS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:E3BYVNFHILDKP5BGOWQLHA7JSS","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":"c2bf275fe66890daff1733eded2e4958b4b70c8f7d6e0a9abe280ed588492a12","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T17:50:51Z","title_canon_sha256":"d875816c820946146d87a3eb23132331c0cd90705dc46e8bb677c6423b32160b"},"schema_version":"1.0","source":{"id":"2507.14121","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.14121","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"arxiv_version","alias_value":"2507.14121v1","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.14121","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"pith_short_12","alias_value":"E3BYVNFHILDK","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"pith_short_16","alias_value":"E3BYVNFHILDKP5BG","created_at":"2026-07-05T11:39:29Z"},{"alias_kind":"pith_short_8","alias_value":"E3BYVNFH","created_at":"2026-07-05T11:39:29Z"}],"graph_snapshots":[{"event_id":"sha256:5b41f8daea9ba83596357ae76fa60713bb680a1da244d1c73c8692bd19ae19b8","target":"graph","created_at":"2026-07-05T11:39:29Z","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/2507.14121/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Kolmogorov Arnold Networks (KANs) are recent architectural advancement in neural computation that offer a mathematically grounded alternative to standard neural networks. This study presents an empirical evaluation of KANs in context of class imbalanced classification, using ten benchmark datasets. We observe that KANs can inherently perform well on raw imbalanced data more effectively than Multi-Layer Perceptrons (MLPs) without any resampling strategy. However, conventional imbalance strategies fundamentally conflict with KANs mathematical structure as resampling and focal loss implementation","authors_text":"Pankaj Yadav, Vivek Vijay","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T17:50:51Z","title":"Kolmogorov Arnold Networks (KANs) for Imbalanced Data -- An Empirical Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.14121","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":"sha256:24e2b99aa77f8fb679e75f7b0d03bb7cde201c1efd6fa26002e343796d0549ff","target":"record","created_at":"2026-07-05T11:39:29Z","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":"c2bf275fe66890daff1733eded2e4958b4b70c8f7d6e0a9abe280ed588492a12","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-18T17:50:51Z","title_canon_sha256":"d875816c820946146d87a3eb23132331c0cd90705dc46e8bb677c6423b32160b"},"schema_version":"1.0","source":{"id":"2507.14121","kind":"arxiv","version":1}},"canonical_sha256":"26c38ab4a742c6a7f42675a0b383e99491e4ff7e3121eed360eceedf72de131a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"26c38ab4a742c6a7f42675a0b383e99491e4ff7e3121eed360eceedf72de131a","first_computed_at":"2026-07-05T11:39:29.026498Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:39:29.026498Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iMudp50klSAOlJDJivkvIUN9yn1olgl7GM+nKtZXCSUjsmKHwm0cxd38S1tSeG4TBBDWzTuENHoyKffixRbxAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:39:29.026918Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.14121","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:24e2b99aa77f8fb679e75f7b0d03bb7cde201c1efd6fa26002e343796d0549ff","sha256:5b41f8daea9ba83596357ae76fa60713bb680a1da244d1c73c8692bd19ae19b8"],"state_sha256":"e78a6738345415058bd5e5e5c79ce3f69912eedf77705c2e1d44f18a5b8950b8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aDW8BAiLHl0uvqQRyJ+AFpVUjEzAT3OrgYQ7juJez6g4QeO5XNJVR0Lsp7qoRLID8lQsaBAX3NH01eIQobphDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T13:40:20.707642Z","bundle_sha256":"1034ec61c647c7ebe7bb31dc25d187758df37e23fafa882e71a2a5898d6b06e8"}}