{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:TKP44RTP7G3ZQ2A7VCB5AKKKDQ","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":"8a49920b658d39e6c6aab42edf17f439a85debe7c1d9d9be45dd4624791b5027","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-05T08:29:33Z","title_canon_sha256":"f749215df9ef314f642df26c944483388a6ea34df7b361676dd5240bd5dae540"},"schema_version":"1.0","source":{"id":"2210.02089","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.02089","created_at":"2026-07-05T05:03:43Z"},{"alias_kind":"arxiv_version","alias_value":"2210.02089v1","created_at":"2026-07-05T05:03:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.02089","created_at":"2026-07-05T05:03:43Z"},{"alias_kind":"pith_short_12","alias_value":"TKP44RTP7G3Z","created_at":"2026-07-05T05:03:43Z"},{"alias_kind":"pith_short_16","alias_value":"TKP44RTP7G3ZQ2A7","created_at":"2026-07-05T05:03:43Z"},{"alias_kind":"pith_short_8","alias_value":"TKP44RTP","created_at":"2026-07-05T05:03:43Z"}],"graph_snapshots":[{"event_id":"sha256:ecc725556610e66af77575e8ca6d832c846cbf925c5d2ef3825cb87abecd051c","target":"graph","created_at":"2026-07-05T05:03:43Z","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/2210.02089/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conditional generation of time-dependent data is a task that has much interest, whether for data augmentation, scenario simulation, completing missing data, or other purposes. Recent works proposed a Transformer-based Time series generative adversarial network (TTS-GAN) to address the limitations of recurrent neural networks. However, this model assumes a unimodal distribution and tries to generate samples around the expectation of the real data distribution. One of its limitations is that it may generate a random multivariate time series; it may fail to generate samples in the presence of mul","authors_text":"Abdellah Madane, Florent Forest, Hanane Azzag, Jerome Lacaille, Mohamed-djallel Dilmi, Mustapha Lebbah","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-05T08:29:33Z","title":"Transformer-based conditional generative adversarial network for multivariate time series generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.02089","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:a8ddf8f6dbfc59c2170fff13b965b4f21e383008e983e27c75cdaadbfd14e159","target":"record","created_at":"2026-07-05T05:03:43Z","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":"8a49920b658d39e6c6aab42edf17f439a85debe7c1d9d9be45dd4624791b5027","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-10-05T08:29:33Z","title_canon_sha256":"f749215df9ef314f642df26c944483388a6ea34df7b361676dd5240bd5dae540"},"schema_version":"1.0","source":{"id":"2210.02089","kind":"arxiv","version":1}},"canonical_sha256":"9a9fce466ff9b798681fa883d0294a1c1af461babbc3c23caa4ec7962d5b88e2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9a9fce466ff9b798681fa883d0294a1c1af461babbc3c23caa4ec7962d5b88e2","first_computed_at":"2026-07-05T05:03:43.141671Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:03:43.141671Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3I2g6INNmxJigZ4SfHBnOPCTUTfAhePBkHc8TdnahdNMogUMn3D6rXlxIQJqoucbKmy+FsZnNKMV7faM2iEZBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:03:43.142076Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.02089","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a8ddf8f6dbfc59c2170fff13b965b4f21e383008e983e27c75cdaadbfd14e159","sha256:ecc725556610e66af77575e8ca6d832c846cbf925c5d2ef3825cb87abecd051c"],"state_sha256":"44e040abdb2f8e51ac037008c4b8cfdc6b4140f8b0667d687676fb6bffffd38c"}