{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:PLTUQVACE4TRL5EX5FCHJ72PMH","short_pith_number":"pith:PLTUQVAC","canonical_record":{"source":{"id":"2406.09087","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-13T13:13:17Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d7a3c2ca750d608045d0d9c1087092038679bea6c955f33b05b67ec9164e4599","abstract_canon_sha256":"24146d51754804bcd2efd7673891a61c47989311e322c55cb2da801253294e46"},"schema_version":"1.0"},"canonical_sha256":"7ae7485402272715f497e94474ff4f61f0d5c96cedb8cae3041beb193b92cdf2","source":{"kind":"arxiv","id":"2406.09087","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.09087","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"arxiv_version","alias_value":"2406.09087v2","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.09087","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"pith_short_12","alias_value":"PLTUQVACE4TR","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"pith_short_16","alias_value":"PLTUQVACE4TRL5EX","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"pith_short_8","alias_value":"PLTUQVAC","created_at":"2026-07-05T09:22:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:PLTUQVACE4TRL5EX5FCHJ72PMH","target":"record","payload":{"canonical_record":{"source":{"id":"2406.09087","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-13T13:13:17Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d7a3c2ca750d608045d0d9c1087092038679bea6c955f33b05b67ec9164e4599","abstract_canon_sha256":"24146d51754804bcd2efd7673891a61c47989311e322c55cb2da801253294e46"},"schema_version":"1.0"},"canonical_sha256":"7ae7485402272715f497e94474ff4f61f0d5c96cedb8cae3041beb193b92cdf2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:22:19.310877Z","signature_b64":"ZUFCu5QvM0bf8UxFsj/+JzghoNyJ2SgLGZiTNFBoqKcnLIdJpqyh8/kM3W23Pzxu+TQmEcpcg4PP9D6W0ZAbBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7ae7485402272715f497e94474ff4f61f0d5c96cedb8cae3041beb193b92cdf2","last_reissued_at":"2026-07-05T09:22:19.310407Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:22:19.310407Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.09087","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:22:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E0sUOxOB/FZPG38nY7h5yEnTnPlJ7AKzksW0LnwMNHXvIC2oI6yUQ9IzlmUMhFMAsB4BcEo5hl+ho2UTOZhrBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:45:07.616605Z"},"content_sha256":"ef38a99185460945518880b673b2c60850ef2e30205f1b74f9687186c53ccfca","schema_version":"1.0","event_id":"sha256:ef38a99185460945518880b673b2c60850ef2e30205f1b74f9687186c53ccfca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:PLTUQVACE4TRL5EX5FCHJ72PMH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Suitability of KANs for Computer Vision: A preliminary investigation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Basim Azam, Naveed Akhtar","submitted_at":"2024-06-13T13:13:17Z","abstract_excerpt":"Kolmogorov-Arnold Networks (KANs) introduce a paradigm of neural modeling that implements learnable functions on the edges of the networks, diverging from the traditional node-centric activations in neural networks. This work assesses the applicability and efficacy of KANs in visual modeling, focusing on fundamental recognition and segmentation tasks. We mainly analyze the performance and efficiency of different network architectures built using KAN concepts along with conventional building blocks of convolutional and linear layers, enabling a comparative analysis with the conventional models."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.09087","kind":"arxiv","version":2},"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/2406.09087/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":"2026-07-05T09:22:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ygwZnMdGqgAi15s2tfl2M5wWi3IA8h7lmfvLKf4ghdknfpJtEJZm4MWTYNKVCn19xbNVGI7IdcnFySrpVMC2DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:45:07.617117Z"},"content_sha256":"3adab25ac8e39b64c9ab6d3c191a4ffeee07c6bea54619cd254fb45461b9eb1b","schema_version":"1.0","event_id":"sha256:3adab25ac8e39b64c9ab6d3c191a4ffeee07c6bea54619cd254fb45461b9eb1b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PLTUQVACE4TRL5EX5FCHJ72PMH/bundle.json","state_url":"https://pith.science/pith/PLTUQVACE4TRL5EX5FCHJ72PMH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PLTUQVACE4TRL5EX5FCHJ72PMH/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":"2026-08-08T04:45:07Z","links":{"resolver":"https://pith.science/pith/PLTUQVACE4TRL5EX5FCHJ72PMH","bundle":"https://pith.science/pith/PLTUQVACE4TRL5EX5FCHJ72PMH/bundle.json","state":"https://pith.science/pith/PLTUQVACE4TRL5EX5FCHJ72PMH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PLTUQVACE4TRL5EX5FCHJ72PMH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PLTUQVACE4TRL5EX5FCHJ72PMH","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":"24146d51754804bcd2efd7673891a61c47989311e322c55cb2da801253294e46","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-13T13:13:17Z","title_canon_sha256":"d7a3c2ca750d608045d0d9c1087092038679bea6c955f33b05b67ec9164e4599"},"schema_version":"1.0","source":{"id":"2406.09087","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.09087","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"arxiv_version","alias_value":"2406.09087v2","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.09087","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"pith_short_12","alias_value":"PLTUQVACE4TR","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"pith_short_16","alias_value":"PLTUQVACE4TRL5EX","created_at":"2026-07-05T09:22:19Z"},{"alias_kind":"pith_short_8","alias_value":"PLTUQVAC","created_at":"2026-07-05T09:22:19Z"}],"graph_snapshots":[{"event_id":"sha256:3adab25ac8e39b64c9ab6d3c191a4ffeee07c6bea54619cd254fb45461b9eb1b","target":"graph","created_at":"2026-07-05T09:22:19Z","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/2406.09087/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Kolmogorov-Arnold Networks (KANs) introduce a paradigm of neural modeling that implements learnable functions on the edges of the networks, diverging from the traditional node-centric activations in neural networks. This work assesses the applicability and efficacy of KANs in visual modeling, focusing on fundamental recognition and segmentation tasks. We mainly analyze the performance and efficiency of different network architectures built using KAN concepts along with conventional building blocks of convolutional and linear layers, enabling a comparative analysis with the conventional models.","authors_text":"Basim Azam, Naveed Akhtar","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-13T13:13:17Z","title":"Suitability of KANs for Computer Vision: A preliminary investigation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.09087","kind":"arxiv","version":2},"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:ef38a99185460945518880b673b2c60850ef2e30205f1b74f9687186c53ccfca","target":"record","created_at":"2026-07-05T09:22:19Z","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":"24146d51754804bcd2efd7673891a61c47989311e322c55cb2da801253294e46","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-06-13T13:13:17Z","title_canon_sha256":"d7a3c2ca750d608045d0d9c1087092038679bea6c955f33b05b67ec9164e4599"},"schema_version":"1.0","source":{"id":"2406.09087","kind":"arxiv","version":2}},"canonical_sha256":"7ae7485402272715f497e94474ff4f61f0d5c96cedb8cae3041beb193b92cdf2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7ae7485402272715f497e94474ff4f61f0d5c96cedb8cae3041beb193b92cdf2","first_computed_at":"2026-07-05T09:22:19.310407Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:22:19.310407Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZUFCu5QvM0bf8UxFsj/+JzghoNyJ2SgLGZiTNFBoqKcnLIdJpqyh8/kM3W23Pzxu+TQmEcpcg4PP9D6W0ZAbBw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:22:19.310877Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.09087","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ef38a99185460945518880b673b2c60850ef2e30205f1b74f9687186c53ccfca","sha256:3adab25ac8e39b64c9ab6d3c191a4ffeee07c6bea54619cd254fb45461b9eb1b"],"state_sha256":"66bd17023428b11cb920c32cecc8072405588ded972069385d0219eb7df1b3e0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"I17FFVttJkgP6xpjXSMi2ZETVw62Wl+MIB77WXVQpvpnmNsgcNVuJwcJCTVz4G7fEgbxYm7C+AfwFDrFlI/oCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T04:45:07.622674Z","bundle_sha256":"65a41395aae4990e80611a229b60fa1300421ef8bdae990511ba8e7dfd50109c"}}