{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:W63RVKMIWTVYTB55EP3BV2OLQ2","short_pith_number":"pith:W63RVKMI","canonical_record":{"source":{"id":"2411.06727","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-11T05:44:48Z","cross_cats_sorted":[],"title_canon_sha256":"8c1ba36f47b1fcb4ea9ef5b4c118aa8e5eb6d928f8f57d1e3087a0470a6d5e12","abstract_canon_sha256":"6e16e152f521b52334f48233585319c0d2637145af01ceca107cd7b1bb8cea19"},"schema_version":"1.0"},"canonical_sha256":"b7b71aa988b4eb8987bd23f61ae9cb86989acb7b8365faa6db57e04425665aee","source":{"kind":"arxiv","id":"2411.06727","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.06727","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"arxiv_version","alias_value":"2411.06727v2","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.06727","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"pith_short_12","alias_value":"W63RVKMIWTVY","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"pith_short_16","alias_value":"W63RVKMIWTVYTB55","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"pith_short_8","alias_value":"W63RVKMI","created_at":"2026-07-05T09:35:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:W63RVKMIWTVYTB55EP3BV2OLQ2","target":"record","payload":{"canonical_record":{"source":{"id":"2411.06727","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-11T05:44:48Z","cross_cats_sorted":[],"title_canon_sha256":"8c1ba36f47b1fcb4ea9ef5b4c118aa8e5eb6d928f8f57d1e3087a0470a6d5e12","abstract_canon_sha256":"6e16e152f521b52334f48233585319c0d2637145af01ceca107cd7b1bb8cea19"},"schema_version":"1.0"},"canonical_sha256":"b7b71aa988b4eb8987bd23f61ae9cb86989acb7b8365faa6db57e04425665aee","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:35:14.753534Z","signature_b64":"wVzQLjIc8BdiqwgzyvWbMDbd8XlcD3PxD0lbmViY16LB9cwQVErj0Wd5opK5nL8WfyXpB/8hxyukgYKhY4F7Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7b71aa988b4eb8987bd23f61ae9cb86989acb7b8365faa6db57e04425665aee","last_reissued_at":"2026-07-05T09:35:14.753050Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:35:14.753050Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.06727","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":"2026-07-05T09:35:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8UZnsgXfN3YagPfDhI+k3vCSzrxp8CoioS7RoRvYruGDEf9Z1NiMLjkBw2Ep16xaTQRXPfUQDgVAF24H4ooxAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:17:20.780930Z"},"content_sha256":"e068fff40dda696e0105de119a049d95fb3fb883b4800a242bfcb64ebfaeb1b5","schema_version":"1.0","event_id":"sha256:e068fff40dda696e0105de119a049d95fb3fb883b4800a242bfcb64ebfaeb1b5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:W63RVKMIWTVYTB55EP3BV2OLQ2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Li Shi, Yueyang Cang, Yu hang liu","submitted_at":"2024-11-11T05:44:48Z","abstract_excerpt":"Kolmogorov-Arnold Networks(KANs), as a theoretically efficient neural network architecture, have garnered attention for their potential in capturing complex patterns. However, their application in computer vision remains relatively unexplored. This study first analyzes the potential of KAN in computer vision tasks, evaluating the performance of KAN and its convolutional variants in image classification and semantic segmentation. The focus is placed on examining their characteristics across varying data scales and noise levels. Results indicate that while KAN exhibits stronger fitting capabilit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.06727","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/2411.06727/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":"2026-07-05T09:35:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BOyCi12/coUyQZKwaXSImyW5tN7iiAsxLkvtJ1yjPQ9qJcV/bK4HmfbI1jbv4q4ZhyMlj2VGZw9EXXLvcjFxAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:17:20.781410Z"},"content_sha256":"02ff334c596e5c5ccf1065f04b7256fd8ed1f491c05d906c351d8b0198a2bd4a","schema_version":"1.0","event_id":"sha256:02ff334c596e5c5ccf1065f04b7256fd8ed1f491c05d906c351d8b0198a2bd4a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W63RVKMIWTVYTB55EP3BV2OLQ2/bundle.json","state_url":"https://pith.science/pith/W63RVKMIWTVYTB55EP3BV2OLQ2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W63RVKMIWTVYTB55EP3BV2OLQ2/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":"2026-08-09T10:17:20Z","links":{"resolver":"https://pith.science/pith/W63RVKMIWTVYTB55EP3BV2OLQ2","bundle":"https://pith.science/pith/W63RVKMIWTVYTB55EP3BV2OLQ2/bundle.json","state":"https://pith.science/pith/W63RVKMIWTVYTB55EP3BV2OLQ2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W63RVKMIWTVYTB55EP3BV2OLQ2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:W63RVKMIWTVYTB55EP3BV2OLQ2","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":"6e16e152f521b52334f48233585319c0d2637145af01ceca107cd7b1bb8cea19","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-11T05:44:48Z","title_canon_sha256":"8c1ba36f47b1fcb4ea9ef5b4c118aa8e5eb6d928f8f57d1e3087a0470a6d5e12"},"schema_version":"1.0","source":{"id":"2411.06727","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.06727","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"arxiv_version","alias_value":"2411.06727v2","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.06727","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"pith_short_12","alias_value":"W63RVKMIWTVY","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"pith_short_16","alias_value":"W63RVKMIWTVYTB55","created_at":"2026-07-05T09:35:14Z"},{"alias_kind":"pith_short_8","alias_value":"W63RVKMI","created_at":"2026-07-05T09:35:14Z"}],"graph_snapshots":[{"event_id":"sha256:02ff334c596e5c5ccf1065f04b7256fd8ed1f491c05d906c351d8b0198a2bd4a","target":"graph","created_at":"2026-07-05T09:35:14Z","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/2411.06727/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Kolmogorov-Arnold Networks(KANs), as a theoretically efficient neural network architecture, have garnered attention for their potential in capturing complex patterns. However, their application in computer vision remains relatively unexplored. This study first analyzes the potential of KAN in computer vision tasks, evaluating the performance of KAN and its convolutional variants in image classification and semantic segmentation. The focus is placed on examining their characteristics across varying data scales and noise levels. Results indicate that while KAN exhibits stronger fitting capabilit","authors_text":"Li Shi, Yueyang Cang, Yu hang liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-11T05:44:48Z","title":"Can KAN Work? Exploring the Potential of Kolmogorov-Arnold Networks in Computer Vision"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.06727","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:e068fff40dda696e0105de119a049d95fb3fb883b4800a242bfcb64ebfaeb1b5","target":"record","created_at":"2026-07-05T09:35:14Z","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":"6e16e152f521b52334f48233585319c0d2637145af01ceca107cd7b1bb8cea19","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-11-11T05:44:48Z","title_canon_sha256":"8c1ba36f47b1fcb4ea9ef5b4c118aa8e5eb6d928f8f57d1e3087a0470a6d5e12"},"schema_version":"1.0","source":{"id":"2411.06727","kind":"arxiv","version":2}},"canonical_sha256":"b7b71aa988b4eb8987bd23f61ae9cb86989acb7b8365faa6db57e04425665aee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7b71aa988b4eb8987bd23f61ae9cb86989acb7b8365faa6db57e04425665aee","first_computed_at":"2026-07-05T09:35:14.753050Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:35:14.753050Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wVzQLjIc8BdiqwgzyvWbMDbd8XlcD3PxD0lbmViY16LB9cwQVErj0Wd5opK5nL8WfyXpB/8hxyukgYKhY4F7Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:35:14.753534Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.06727","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e068fff40dda696e0105de119a049d95fb3fb883b4800a242bfcb64ebfaeb1b5","sha256:02ff334c596e5c5ccf1065f04b7256fd8ed1f491c05d906c351d8b0198a2bd4a"],"state_sha256":"3644eba4bd94edf19e59ed8bee1d99ba108c5932e519fb4b8fdfe81b20a6d7b2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZzJlwCzmQS6VfyPFkrLQeIkoTr+q2cAiy0ugJ67LzYn9neI3cWSO3BfQjWuwga6Nhl1W3T0HmE8a6PAnT7QTDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T10:17:20.784565Z","bundle_sha256":"a6e0e0acd6d1b43a38b60e3d937203af244554db6e2b40e4cac2991544d04f43"}}