{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:BDPETZBYOYUT6UAE5ME2D4ORXX","short_pith_number":"pith:BDPETZBY","canonical_record":{"source":{"id":"2408.05681","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-11T03:26:22Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4c2564d9b7d255b2a2eb3de9d09381949825a43e8ed94d82378ed56370f013fa","abstract_canon_sha256":"557ff3e7efa0b1a788d2425dcf5347cd15e1a70929e9e490aac361b56c300cee"},"schema_version":"1.0"},"canonical_sha256":"08de49e43876293f5004eb09a1f1d1bde5f876f5f7fbc75ce8ad49e17db4f487","source":{"kind":"arxiv","id":"2408.05681","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.05681","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"arxiv_version","alias_value":"2408.05681v1","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.05681","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"pith_short_12","alias_value":"BDPETZBYOYUT","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"pith_short_16","alias_value":"BDPETZBYOYUT6UAE","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"pith_short_8","alias_value":"BDPETZBY","created_at":"2026-07-05T08:54:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:BDPETZBYOYUT6UAE5ME2D4ORXX","target":"record","payload":{"canonical_record":{"source":{"id":"2408.05681","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-11T03:26:22Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4c2564d9b7d255b2a2eb3de9d09381949825a43e8ed94d82378ed56370f013fa","abstract_canon_sha256":"557ff3e7efa0b1a788d2425dcf5347cd15e1a70929e9e490aac361b56c300cee"},"schema_version":"1.0"},"canonical_sha256":"08de49e43876293f5004eb09a1f1d1bde5f876f5f7fbc75ce8ad49e17db4f487","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:54:23.585815Z","signature_b64":"DtHAv+xujKzelvMGMQP8LazBGMCVW45aMZANOhylUUtyFxo956K5Zb8hKOZJDVgVgFFfNAMib5kTJD52x69ICQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08de49e43876293f5004eb09a1f1d1bde5f876f5f7fbc75ce8ad49e17db4f487","last_reissued_at":"2026-07-05T08:54:23.585479Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:54:23.585479Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.05681","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":"2026-07-05T08:54:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u7rhJZHVGY7k4d/vgW3VP088RKN6u+w+NaQnkZ2ZLXQEIZtv7DWgiF/HGx4d6o2gAXVBdvyocZw9Rthhs+3NDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T19:48:02.243158Z"},"content_sha256":"5e469b659fd29087bab1fc7b051626b0f2436cf603db7fefd462014a928bc864","schema_version":"1.0","event_id":"sha256:5e469b659fd29087bab1fc7b051626b0f2436cf603db7fefd462014a928bc864"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:BDPETZBYOYUT6UAE5ME2D4ORXX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SRTFD: Scalable Real-Time Fault Diagnosis through Online Continual Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Dandan Zhao, Hongpeng Yin, Karthick Sharma, Shuhao Zhang, Yuxin Qi","submitted_at":"2024-08-11T03:26:22Z","abstract_excerpt":"Fault diagnosis (FD) is essential for maintaining operational safety and minimizing economic losses by detecting system abnormalities. Recently, deep learning (DL)-driven FD methods have gained prominence, offering significant improvements in precision and adaptability through the utilization of extensive datasets and advanced DL models. Modern industrial environments, however, demand FD methods that can handle new fault types, dynamic conditions, large-scale data, and provide real-time responses with minimal prior information. Although online continual learning (OCL) demonstrates potential in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.05681","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/2408.05681/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":"2026-07-05T08:54:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G4AmvnQHlD+VEvn5Zn09kCIXn4uNuxKpw/zN1rK/zGSbnDKhmtCV/p78NGuyZ8vETcuutbIdKyrgdAsI0paABg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T19:48:02.243733Z"},"content_sha256":"7b7f967559a34d2df6c9eebcf18c0ae52ec5404134763dce8d68fb72c93ba2e0","schema_version":"1.0","event_id":"sha256:7b7f967559a34d2df6c9eebcf18c0ae52ec5404134763dce8d68fb72c93ba2e0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BDPETZBYOYUT6UAE5ME2D4ORXX/bundle.json","state_url":"https://pith.science/pith/BDPETZBYOYUT6UAE5ME2D4ORXX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BDPETZBYOYUT6UAE5ME2D4ORXX/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":"2026-08-11T19:48:02Z","links":{"resolver":"https://pith.science/pith/BDPETZBYOYUT6UAE5ME2D4ORXX","bundle":"https://pith.science/pith/BDPETZBYOYUT6UAE5ME2D4ORXX/bundle.json","state":"https://pith.science/pith/BDPETZBYOYUT6UAE5ME2D4ORXX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BDPETZBYOYUT6UAE5ME2D4ORXX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BDPETZBYOYUT6UAE5ME2D4ORXX","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":"557ff3e7efa0b1a788d2425dcf5347cd15e1a70929e9e490aac361b56c300cee","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-11T03:26:22Z","title_canon_sha256":"4c2564d9b7d255b2a2eb3de9d09381949825a43e8ed94d82378ed56370f013fa"},"schema_version":"1.0","source":{"id":"2408.05681","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.05681","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"arxiv_version","alias_value":"2408.05681v1","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.05681","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"pith_short_12","alias_value":"BDPETZBYOYUT","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"pith_short_16","alias_value":"BDPETZBYOYUT6UAE","created_at":"2026-07-05T08:54:23Z"},{"alias_kind":"pith_short_8","alias_value":"BDPETZBY","created_at":"2026-07-05T08:54:23Z"}],"graph_snapshots":[{"event_id":"sha256:7b7f967559a34d2df6c9eebcf18c0ae52ec5404134763dce8d68fb72c93ba2e0","target":"graph","created_at":"2026-07-05T08:54:23Z","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/2408.05681/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fault diagnosis (FD) is essential for maintaining operational safety and minimizing economic losses by detecting system abnormalities. Recently, deep learning (DL)-driven FD methods have gained prominence, offering significant improvements in precision and adaptability through the utilization of extensive datasets and advanced DL models. Modern industrial environments, however, demand FD methods that can handle new fault types, dynamic conditions, large-scale data, and provide real-time responses with minimal prior information. Although online continual learning (OCL) demonstrates potential in","authors_text":"Dandan Zhao, Hongpeng Yin, Karthick Sharma, Shuhao Zhang, Yuxin Qi","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-11T03:26:22Z","title":"SRTFD: Scalable Real-Time Fault Diagnosis through Online Continual Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.05681","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":"sha256:5e469b659fd29087bab1fc7b051626b0f2436cf603db7fefd462014a928bc864","target":"record","created_at":"2026-07-05T08:54:23Z","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":"557ff3e7efa0b1a788d2425dcf5347cd15e1a70929e9e490aac361b56c300cee","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-08-11T03:26:22Z","title_canon_sha256":"4c2564d9b7d255b2a2eb3de9d09381949825a43e8ed94d82378ed56370f013fa"},"schema_version":"1.0","source":{"id":"2408.05681","kind":"arxiv","version":1}},"canonical_sha256":"08de49e43876293f5004eb09a1f1d1bde5f876f5f7fbc75ce8ad49e17db4f487","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"08de49e43876293f5004eb09a1f1d1bde5f876f5f7fbc75ce8ad49e17db4f487","first_computed_at":"2026-07-05T08:54:23.585479Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:54:23.585479Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DtHAv+xujKzelvMGMQP8LazBGMCVW45aMZANOhylUUtyFxo956K5Zb8hKOZJDVgVgFFfNAMib5kTJD52x69ICQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:54:23.585815Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.05681","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5e469b659fd29087bab1fc7b051626b0f2436cf603db7fefd462014a928bc864","sha256:7b7f967559a34d2df6c9eebcf18c0ae52ec5404134763dce8d68fb72c93ba2e0"],"state_sha256":"ec0f778939d690aa182382bbeb047f115969442e775cd87c2745caafce1a82ee"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gokyDCqMLEFWy4c90Iy2lAG5pT8myS1XNXpcl0YsT654jrynVBdeUmtOpVxAlluazt/xUVLVUYQj4fXjlvpXCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T19:48:02.247394Z","bundle_sha256":"0db9da6a08e922d1705839ba735da2e55901af168114cba6290bb07ea781770b"}}