{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:WG6X3EFQDRQSY5LXRXY2WD2URW","short_pith_number":"pith:WG6X3EFQ","canonical_record":{"source":{"id":"2504.16432","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-23T05:34:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"7b878061344f549aa5049add9d5616552bc19a64001cef9f48d7f89fcc2f9d60","abstract_canon_sha256":"c4877adc68a35beccb139804e0941a4b13512f7cd98e1bdadedfa1b478ef536a"},"schema_version":"1.0"},"canonical_sha256":"b1bd7d90b01c612c75778df1ab0f548d8b166721f868796fa732ac2e59e83d8c","source":{"kind":"arxiv","id":"2504.16432","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.16432","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"arxiv_version","alias_value":"2504.16432v2","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.16432","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"pith_short_12","alias_value":"WG6X3EFQDRQS","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"pith_short_16","alias_value":"WG6X3EFQDRQSY5LX","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"pith_short_8","alias_value":"WG6X3EFQ","created_at":"2026-07-05T11:50:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:WG6X3EFQDRQSY5LXRXY2WD2URW","target":"record","payload":{"canonical_record":{"source":{"id":"2504.16432","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-23T05:34:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"7b878061344f549aa5049add9d5616552bc19a64001cef9f48d7f89fcc2f9d60","abstract_canon_sha256":"c4877adc68a35beccb139804e0941a4b13512f7cd98e1bdadedfa1b478ef536a"},"schema_version":"1.0"},"canonical_sha256":"b1bd7d90b01c612c75778df1ab0f548d8b166721f868796fa732ac2e59e83d8c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:50:35.616124Z","signature_b64":"tNyg+hJAuOHwLmcL+JbA4IuN2HLGcTPVSsPdezyNAd0onY4eHvOJGNfDD/LiuaDXduW53NlwPDsv0rdSM0ehCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b1bd7d90b01c612c75778df1ab0f548d8b166721f868796fa732ac2e59e83d8c","last_reissued_at":"2026-07-05T11:50:35.615611Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:50:35.615611Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.16432","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":"2026-07-05T11:50:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zwXCGdqxeGFb593pVWTwr67x2xzxzHz90qOEyo/Eep3ejpHqm16WOqEAxtNn4AzDJ2MERW7jXWqXmKquxkeRAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T06:54:46.092705Z"},"content_sha256":"a8aea1f7f76e813eca972f6858d02151296198f73870af8baa6a632d68d805bb","schema_version":"1.0","event_id":"sha256:a8aea1f7f76e813eca972f6858d02151296198f73870af8baa6a632d68d805bb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:WG6X3EFQDRQSY5LXRXY2WD2URW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"iTFKAN: Interpretable Time Series Forecasting with Kolmogorov-Arnold Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Rui An, Wenqi Fan, Yanghui Rao, Yuxuan Liang, Ziran Liang","submitted_at":"2025-04-23T05:34:49Z","abstract_excerpt":"As time evolves, data within specific domains exhibit predictability that motivates time series forecasting to predict future trends from historical data. However, current deep forecasting methods can achieve promising performance but generally lack interpretability, hindering trustworthiness and practical deployment in safety-critical applications such as auto-driving and healthcare. In this paper, we propose a novel interpretable model, iTFKAN, for credible time series forecasting. iTFKAN enables further exploration of model decision rationales and underlying data patterns due to its interpr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.16432","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/2504.16432/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":"2026-07-05T11:50:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nq5tRAmqIfnqFiXaVK5+bok8T5+CGWb6NMde/itJz3BiKhqJ2XQbZ7RcgkodIw9x5sLBaNs0uRvL3NE1iCeiAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T06:54:46.093236Z"},"content_sha256":"cb3dd6e60a29bdcbfbad4946badaadac5c5a4da152e1d697ea1b2d5958108148","schema_version":"1.0","event_id":"sha256:cb3dd6e60a29bdcbfbad4946badaadac5c5a4da152e1d697ea1b2d5958108148"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WG6X3EFQDRQSY5LXRXY2WD2URW/bundle.json","state_url":"https://pith.science/pith/WG6X3EFQDRQSY5LXRXY2WD2URW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WG6X3EFQDRQSY5LXRXY2WD2URW/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":"2026-08-09T06:54:46Z","links":{"resolver":"https://pith.science/pith/WG6X3EFQDRQSY5LXRXY2WD2URW","bundle":"https://pith.science/pith/WG6X3EFQDRQSY5LXRXY2WD2URW/bundle.json","state":"https://pith.science/pith/WG6X3EFQDRQSY5LXRXY2WD2URW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WG6X3EFQDRQSY5LXRXY2WD2URW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WG6X3EFQDRQSY5LXRXY2WD2URW","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":"c4877adc68a35beccb139804e0941a4b13512f7cd98e1bdadedfa1b478ef536a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-23T05:34:49Z","title_canon_sha256":"7b878061344f549aa5049add9d5616552bc19a64001cef9f48d7f89fcc2f9d60"},"schema_version":"1.0","source":{"id":"2504.16432","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.16432","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"arxiv_version","alias_value":"2504.16432v2","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.16432","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"pith_short_12","alias_value":"WG6X3EFQDRQS","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"pith_short_16","alias_value":"WG6X3EFQDRQSY5LX","created_at":"2026-07-05T11:50:35Z"},{"alias_kind":"pith_short_8","alias_value":"WG6X3EFQ","created_at":"2026-07-05T11:50:35Z"}],"graph_snapshots":[{"event_id":"sha256:cb3dd6e60a29bdcbfbad4946badaadac5c5a4da152e1d697ea1b2d5958108148","target":"graph","created_at":"2026-07-05T11:50:35Z","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/2504.16432/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As time evolves, data within specific domains exhibit predictability that motivates time series forecasting to predict future trends from historical data. However, current deep forecasting methods can achieve promising performance but generally lack interpretability, hindering trustworthiness and practical deployment in safety-critical applications such as auto-driving and healthcare. In this paper, we propose a novel interpretable model, iTFKAN, for credible time series forecasting. iTFKAN enables further exploration of model decision rationales and underlying data patterns due to its interpr","authors_text":"Rui An, Wenqi Fan, Yanghui Rao, Yuxuan Liang, Ziran Liang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-23T05:34:49Z","title":"iTFKAN: Interpretable Time Series Forecasting with Kolmogorov-Arnold Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.16432","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:a8aea1f7f76e813eca972f6858d02151296198f73870af8baa6a632d68d805bb","target":"record","created_at":"2026-07-05T11:50:35Z","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":"c4877adc68a35beccb139804e0941a4b13512f7cd98e1bdadedfa1b478ef536a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-04-23T05:34:49Z","title_canon_sha256":"7b878061344f549aa5049add9d5616552bc19a64001cef9f48d7f89fcc2f9d60"},"schema_version":"1.0","source":{"id":"2504.16432","kind":"arxiv","version":2}},"canonical_sha256":"b1bd7d90b01c612c75778df1ab0f548d8b166721f868796fa732ac2e59e83d8c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b1bd7d90b01c612c75778df1ab0f548d8b166721f868796fa732ac2e59e83d8c","first_computed_at":"2026-07-05T11:50:35.615611Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:50:35.615611Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tNyg+hJAuOHwLmcL+JbA4IuN2HLGcTPVSsPdezyNAd0onY4eHvOJGNfDD/LiuaDXduW53NlwPDsv0rdSM0ehCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:50:35.616124Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.16432","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a8aea1f7f76e813eca972f6858d02151296198f73870af8baa6a632d68d805bb","sha256:cb3dd6e60a29bdcbfbad4946badaadac5c5a4da152e1d697ea1b2d5958108148"],"state_sha256":"9fb19ad41b0eea20e60e411020e7f0ce130f048f2ba73feabeae7780852373a4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NO06CPC6UG6UQSOfNdfAZa0SVY4RcYXzB/HaNQ5kSbYCtBuztwQvMr1+QWzczgD5y7TYedOpek5V8MXo1Io2Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T06:54:46.098851Z","bundle_sha256":"c4bebf27bfad1dd39e4038f83e7f2b96d98434b03384d6d23efbca770d6d7f60"}}