{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:E276PPTDF7F3ALHNW5YHXHJUGW","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":"0581dd2f59aa74f2d907cde1bc7415411ade1c643e577ff6e95f436f80b256d9","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-15T19:54:53Z","title_canon_sha256":"2945eb7eaf1ef195e3729c485a07c607dcf638bba272ec2d3f71c2a8ce27c703"},"schema_version":"1.0","source":{"id":"2408.08399","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.08399","created_at":"2026-05-26T02:04:58Z"},{"alias_kind":"arxiv_version","alias_value":"2408.08399v3","created_at":"2026-05-26T02:04:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.08399","created_at":"2026-05-26T02:04:58Z"},{"alias_kind":"pith_short_12","alias_value":"E276PPTDF7F3","created_at":"2026-05-26T02:04:58Z"},{"alias_kind":"pith_short_16","alias_value":"E276PPTDF7F3ALHN","created_at":"2026-05-26T02:04:58Z"},{"alias_kind":"pith_short_8","alias_value":"E276PPTD","created_at":"2026-05-26T02:04:58Z"}],"graph_snapshots":[{"event_id":"sha256:f8426f92f398b178dd23c95fe17f50f1d2f6d84b82970ac794e3bb331ce8c325","target":"graph","created_at":"2026-05-26T02:04:58Z","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/2408.08399/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Electricity Consumption Profiles (ECPs) are crucial for operating and planning power distribution systems, especially with the increasing number of low-carbon technologies such as solar panels and electric vehicles. Traditional ECP modeling methods typically assume the availability of sufficient ECP data. However, in practice, the accessibility of ECP data is limited due to privacy issues or the absence of metering devices. Few-shot learning (FSL) has emerged as a promising solution for ECP modeling in data-scarce scenarios. Nevertheless, standard FSL methods, such as those used for images, ar","authors_text":"Chenguang Wang, Eric Pauwels, Gao Peng, Pedro P. Vergara, Peter Palensky, Weijie Xia","cross_cats":["cs.SY","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-15T19:54:53Z","title":"Transformer-based few-shot learning for modeling Electricity Consumption Profiles with minimal data across thousands of domains"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.08399","kind":"arxiv","version":3},"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":"sha256:16b6ff5cbbddccd9de78bc29226ff7e6086dc590b92b1863a575c63a325d2fce","target":"record","created_at":"2026-05-26T02:04:58Z","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":"0581dd2f59aa74f2d907cde1bc7415411ade1c643e577ff6e95f436f80b256d9","cross_cats_sorted":["cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-15T19:54:53Z","title_canon_sha256":"2945eb7eaf1ef195e3729c485a07c607dcf638bba272ec2d3f71c2a8ce27c703"},"schema_version":"1.0","source":{"id":"2408.08399","kind":"arxiv","version":3}},"canonical_sha256":"26bfe7be632fcbb02cedb7707b9d343587f830e7a6e82965b883f0a7b6295e6e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"26bfe7be632fcbb02cedb7707b9d343587f830e7a6e82965b883f0a7b6295e6e","first_computed_at":"2026-05-26T02:04:58.846137Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T02:04:58.846137Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZewEOJDdnMuie2GWp/6KR0BeWKtOz/eFmacvzY9fwxkFGBKO71zhLbm6AJ3uJ0CtcBqK/ilxBiE6SvxqcPPgDw==","signature_status":"signed_v1","signed_at":"2026-05-26T02:04:58.847067Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.08399","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:16b6ff5cbbddccd9de78bc29226ff7e6086dc590b92b1863a575c63a325d2fce","sha256:f8426f92f398b178dd23c95fe17f50f1d2f6d84b82970ac794e3bb331ce8c325"],"state_sha256":"8d4ae36c6e3f7293473936f16c122f0aa4727ea64e1273283feb282d78c47423"}