{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:VCFZAJB2VLXWPPJ6M6RRITJ3HG","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":"436a854b17b59903bf9924ff8f5d7a72a625770048d6ca6a19957c2e71d724b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-10T09:21:28Z","title_canon_sha256":"e39e40482f1d8e80579abdd3d7fee4c996f9fd240a351e93e29907d2a3f53efc"},"schema_version":"1.0","source":{"id":"2606.11844","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.11844","created_at":"2026-06-11T01:10:11Z"},{"alias_kind":"arxiv_version","alias_value":"2606.11844v1","created_at":"2026-06-11T01:10:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.11844","created_at":"2026-06-11T01:10:11Z"},{"alias_kind":"pith_short_12","alias_value":"VCFZAJB2VLXW","created_at":"2026-06-11T01:10:11Z"},{"alias_kind":"pith_short_16","alias_value":"VCFZAJB2VLXWPPJ6","created_at":"2026-06-11T01:10:11Z"},{"alias_kind":"pith_short_8","alias_value":"VCFZAJB2","created_at":"2026-06-11T01:10:11Z"}],"graph_snapshots":[{"event_id":"sha256:4211e19a79edb9d5976152266e5e24dc37795b844eddab5016a179d2df3b363f","target":"graph","created_at":"2026-06-11T01:10:11Z","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/2606.11844/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Continual anomaly detection in tabular data is challenging and remains largely underexplored, particularly in settings with heterogeneous feature schemas, distribution shifts, and severe class imbalance. In many real-world applications, data arrive sequentially from diverse domains, rendering conventional continual learning methods ineffective due to their reliance on a fixed input space. We propose a continual learning (CL) method, which can overcome these challenges and continually learn from different tasks. Our method consists of three main parts: our AGF model, Taskfusion augmentation, an","authors_text":"Andreas Dengel, Dayananda Herurkar, Federico Raue, Joachim Folz, J\\\"orn Hees","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-10T09:21:28Z","title":"TaskFusion: Continual Anomaly Detection for Heterogeneous Tabular Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.11844","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":"sha256:048a3f0f1fd6d992fef41a9ba662daafaf53d23d9e986b461a0bea5663bb664a","target":"record","created_at":"2026-06-11T01:10:11Z","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":"436a854b17b59903bf9924ff8f5d7a72a625770048d6ca6a19957c2e71d724b5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-10T09:21:28Z","title_canon_sha256":"e39e40482f1d8e80579abdd3d7fee4c996f9fd240a351e93e29907d2a3f53efc"},"schema_version":"1.0","source":{"id":"2606.11844","kind":"arxiv","version":1}},"canonical_sha256":"a88b90243aaaef67bd3e67a3144d3b398b8c990e15a018b280aabd84ff168c70","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a88b90243aaaef67bd3e67a3144d3b398b8c990e15a018b280aabd84ff168c70","first_computed_at":"2026-06-11T01:10:11.342075Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-11T01:10:11.342075Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"a6J6vrmRnjaB9onO5Xy2GMXhNXqxhgGZq2kARQidXAkFKDGjQ4lewTt/yAODyGmAHn4vx4bjU9LDT6cx/proCg==","signature_status":"signed_v1","signed_at":"2026-06-11T01:10:11.342909Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.11844","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:048a3f0f1fd6d992fef41a9ba662daafaf53d23d9e986b461a0bea5663bb664a","sha256:4211e19a79edb9d5976152266e5e24dc37795b844eddab5016a179d2df3b363f"],"state_sha256":"9becc2cf1665fce81fb2291738a12f33433e72d619cabcb4195abb4e41b8fa20"}