{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:TMX52YNERD424WORHAKVNB646L","short_pith_number":"pith:TMX52YNE","canonical_record":{"source":{"id":"2606.13277","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2026-06-11T12:30:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e6ffa9dcf7a9459184c4a4c5e52b1ae6b22864240b3283a274bf4f17775f2936","abstract_canon_sha256":"142ed005321db40d3462bdf7d72d23699db5bdf6970ef11d60dcbe5cac4eb54a"},"schema_version":"1.0"},"canonical_sha256":"9b2fdd61a488f9ae59d138155687dcf2efc455db2233371e15ad6527f4cf462a","source":{"kind":"arxiv","id":"2606.13277","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.13277","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"arxiv_version","alias_value":"2606.13277v1","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.13277","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"pith_short_12","alias_value":"TMX52YNERD42","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"pith_short_16","alias_value":"TMX52YNERD424WOR","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"pith_short_8","alias_value":"TMX52YNE","created_at":"2026-06-12T01:09:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:TMX52YNERD424WORHAKVNB646L","target":"record","payload":{"canonical_record":{"source":{"id":"2606.13277","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2026-06-11T12:30:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e6ffa9dcf7a9459184c4a4c5e52b1ae6b22864240b3283a274bf4f17775f2936","abstract_canon_sha256":"142ed005321db40d3462bdf7d72d23699db5bdf6970ef11d60dcbe5cac4eb54a"},"schema_version":"1.0"},"canonical_sha256":"9b2fdd61a488f9ae59d138155687dcf2efc455db2233371e15ad6527f4cf462a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-12T01:09:50.164002Z","signature_b64":"I5sueengMXzquXACtcxR2Q09jaaFhZzKElR3fmN3AYC+wC2puC8Ji2+JIRBJlBbcdSFG3Q+9W0LGtTTRjCkBBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9b2fdd61a488f9ae59d138155687dcf2efc455db2233371e15ad6527f4cf462a","last_reissued_at":"2026-06-12T01:09:50.163308Z","signature_status":"signed_v1","first_computed_at":"2026-06-12T01:09:50.163308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.13277","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":"2026-06-12T01:09:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZaNl5j/Uqs5I/xblvdJXWgDri4E7RIUtpvXXGlNkVTi83euXcwMXPwkvDkO04y11GsvP9lwL/McBu+sdCGjiCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T14:00:42.152093Z"},"content_sha256":"6811be61cb02fd3749157bc84d3e9e61bdac138f5f9d1bb83efa606f3d0f7d5d","schema_version":"1.0","event_id":"sha256:6811be61cb02fd3749157bc84d3e9e61bdac138f5f9d1bb83efa606f3d0f7d5d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:TMX52YNERD424WORHAKVNB646L","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ProtoX-AD: Self-Explainable Time Series Anomaly Detection and Characterization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Aitor S\\'anchez-Ferrera, Elisabeth Wetzer, Kristoffer Wickstr{\\o}m, Michael Kampffmeyer, Robert Jenssen","submitted_at":"2026-06-11T12:30:40Z","abstract_excerpt":"Recent advances in time series anomaly detection (TSAD) have highlighted the effectiveness of self-supervised classification-based approaches. These methods apply transformations to normal training samples, training a classifier to recognize transformation-specific patterns that help identify anomalies through increased classification errors. Despite their strong performance, a significant challenge is their lack of explainability, as they provide limited insight into the characteristics of flagged anomalies. To address this limitation, we propose ProtoX-AD, a prototype-based self-explainable "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.13277","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/2606.13277/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":"2026-06-12T01:09:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qwVp9QLXV/AWLPkKHgG/ryt2PVgxyG8+5ShtPnli7XkfJk93o0sXPFVN0pvCUJpTkh5i+Vdbe8m/wCaJwp7RDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T14:00:42.152494Z"},"content_sha256":"1840b0629144db9f7b71b8eb181a8a07d5c2ec52e9264b584af8708d1ef004af","schema_version":"1.0","event_id":"sha256:1840b0629144db9f7b71b8eb181a8a07d5c2ec52e9264b584af8708d1ef004af"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TMX52YNERD424WORHAKVNB646L/bundle.json","state_url":"https://pith.science/pith/TMX52YNERD424WORHAKVNB646L/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TMX52YNERD424WORHAKVNB646L/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":"2026-06-22T14:00:42Z","links":{"resolver":"https://pith.science/pith/TMX52YNERD424WORHAKVNB646L","bundle":"https://pith.science/pith/TMX52YNERD424WORHAKVNB646L/bundle.json","state":"https://pith.science/pith/TMX52YNERD424WORHAKVNB646L/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TMX52YNERD424WORHAKVNB646L/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:TMX52YNERD424WORHAKVNB646L","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":"142ed005321db40d3462bdf7d72d23699db5bdf6970ef11d60dcbe5cac4eb54a","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2026-06-11T12:30:40Z","title_canon_sha256":"e6ffa9dcf7a9459184c4a4c5e52b1ae6b22864240b3283a274bf4f17775f2936"},"schema_version":"1.0","source":{"id":"2606.13277","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.13277","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"arxiv_version","alias_value":"2606.13277v1","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.13277","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"pith_short_12","alias_value":"TMX52YNERD42","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"pith_short_16","alias_value":"TMX52YNERD424WOR","created_at":"2026-06-12T01:09:50Z"},{"alias_kind":"pith_short_8","alias_value":"TMX52YNE","created_at":"2026-06-12T01:09:50Z"}],"graph_snapshots":[{"event_id":"sha256:1840b0629144db9f7b71b8eb181a8a07d5c2ec52e9264b584af8708d1ef004af","target":"graph","created_at":"2026-06-12T01:09:50Z","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/2606.13277/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in time series anomaly detection (TSAD) have highlighted the effectiveness of self-supervised classification-based approaches. These methods apply transformations to normal training samples, training a classifier to recognize transformation-specific patterns that help identify anomalies through increased classification errors. Despite their strong performance, a significant challenge is their lack of explainability, as they provide limited insight into the characteristics of flagged anomalies. To address this limitation, we propose ProtoX-AD, a prototype-based self-explainable ","authors_text":"Aitor S\\'anchez-Ferrera, Elisabeth Wetzer, Kristoffer Wickstr{\\o}m, Michael Kampffmeyer, Robert Jenssen","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2026-06-11T12:30:40Z","title":"ProtoX-AD: Self-Explainable Time Series Anomaly Detection and Characterization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.13277","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":"sha256:6811be61cb02fd3749157bc84d3e9e61bdac138f5f9d1bb83efa606f3d0f7d5d","target":"record","created_at":"2026-06-12T01:09:50Z","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":"142ed005321db40d3462bdf7d72d23699db5bdf6970ef11d60dcbe5cac4eb54a","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2026-06-11T12:30:40Z","title_canon_sha256":"e6ffa9dcf7a9459184c4a4c5e52b1ae6b22864240b3283a274bf4f17775f2936"},"schema_version":"1.0","source":{"id":"2606.13277","kind":"arxiv","version":1}},"canonical_sha256":"9b2fdd61a488f9ae59d138155687dcf2efc455db2233371e15ad6527f4cf462a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9b2fdd61a488f9ae59d138155687dcf2efc455db2233371e15ad6527f4cf462a","first_computed_at":"2026-06-12T01:09:50.163308Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-12T01:09:50.163308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"I5sueengMXzquXACtcxR2Q09jaaFhZzKElR3fmN3AYC+wC2puC8Ji2+JIRBJlBbcdSFG3Q+9W0LGtTTRjCkBBA==","signature_status":"signed_v1","signed_at":"2026-06-12T01:09:50.164002Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.13277","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6811be61cb02fd3749157bc84d3e9e61bdac138f5f9d1bb83efa606f3d0f7d5d","sha256:1840b0629144db9f7b71b8eb181a8a07d5c2ec52e9264b584af8708d1ef004af"],"state_sha256":"45da9badb8febe623e862ec84bc0458a916e29ab980a9c317e0d83c844889c00"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DISqfL2u4UTD5HIIojOYkg5Orka71cCN3jpcvn3QYpFRi8/xPxlpjSghJ5WadgtBgYsZHgLVV1YiULEBGUDUDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-22T14:00:42.154543Z","bundle_sha256":"59a28175e102d65168417eb5f9898965fa9b26125d87102baaf7ab40cc466276"}}