{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:HBUSYITDB6SU4WFL2QRAPBAWEE","short_pith_number":"pith:HBUSYITD","schema_version":"1.0","canonical_sha256":"38692c22630fa54e58abd4220784162119fcf0f7fce970bfb0232d2e37ec74b4","source":{"kind":"arxiv","id":"2505.16577","version":1},"attestation_state":"computed","paper":{"title":"Large Language Model-Empowered Interactive Load Forecasting","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Dalin Qin, Yi Wang, Yu Zuo","submitted_at":"2025-05-22T12:11:10Z","abstract_excerpt":"The growing complexity of power systems has made accurate load forecasting more important than ever. An increasing number of advanced load forecasting methods have been developed. However, the static design of current methods offers no mechanism for human-model interaction. As the primary users of forecasting models, system operators often find it difficult to understand and apply these advanced models, which typically requires expertise in artificial intelligence (AI). This also prevents them from incorporating their experience and real-world contextual understanding into the forecasting proc"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2505.16577","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-22T12:11:10Z","cross_cats_sorted":[],"title_canon_sha256":"89e0aa80c8a5d77cf4690b1e26fd0e087b6c5f0a1c7897b4206f8dec47091451","abstract_canon_sha256":"0e742cd92cac3af73fbe72a4001941004e593c65e23c794b6647fb14500f7139"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:07:37.335854Z","signature_b64":"XATGg/uRv1TF8UURgP1jAILWW37oAZl+9xpWX7sWuKL7cvb4eV29VEchlfd4dyCSLIhLX0YwyTkh7AnsIg/5Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"38692c22630fa54e58abd4220784162119fcf0f7fce970bfb0232d2e37ec74b4","last_reissued_at":"2026-07-05T11:07:37.335028Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:07:37.335028Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Large Language Model-Empowered Interactive Load Forecasting","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Dalin Qin, Yi Wang, Yu Zuo","submitted_at":"2025-05-22T12:11:10Z","abstract_excerpt":"The growing complexity of power systems has made accurate load forecasting more important than ever. An increasing number of advanced load forecasting methods have been developed. However, the static design of current methods offers no mechanism for human-model interaction. As the primary users of forecasting models, system operators often find it difficult to understand and apply these advanced models, which typically requires expertise in artificial intelligence (AI). This also prevents them from incorporating their experience and real-world contextual understanding into the forecasting proc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.16577","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/2505.16577/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2505.16577","created_at":"2026-07-05T11:07:37.335104+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.16577v1","created_at":"2026-07-05T11:07:37.335104+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.16577","created_at":"2026-07-05T11:07:37.335104+00:00"},{"alias_kind":"pith_short_12","alias_value":"HBUSYITDB6SU","created_at":"2026-07-05T11:07:37.335104+00:00"},{"alias_kind":"pith_short_16","alias_value":"HBUSYITDB6SU4WFL","created_at":"2026-07-05T11:07:37.335104+00:00"},{"alias_kind":"pith_short_8","alias_value":"HBUSYITD","created_at":"2026-07-05T11:07:37.335104+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HBUSYITDB6SU4WFL2QRAPBAWEE","json":"https://pith.science/pith/HBUSYITDB6SU4WFL2QRAPBAWEE.json","graph_json":"https://pith.science/api/pith-number/HBUSYITDB6SU4WFL2QRAPBAWEE/graph.json","events_json":"https://pith.science/api/pith-number/HBUSYITDB6SU4WFL2QRAPBAWEE/events.json","paper":"https://pith.science/paper/HBUSYITD"},"agent_actions":{"view_html":"https://pith.science/pith/HBUSYITDB6SU4WFL2QRAPBAWEE","download_json":"https://pith.science/pith/HBUSYITDB6SU4WFL2QRAPBAWEE.json","view_paper":"https://pith.science/paper/HBUSYITD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.16577&json=true","fetch_graph":"https://pith.science/api/pith-number/HBUSYITDB6SU4WFL2QRAPBAWEE/graph.json","fetch_events":"https://pith.science/api/pith-number/HBUSYITDB6SU4WFL2QRAPBAWEE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HBUSYITDB6SU4WFL2QRAPBAWEE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HBUSYITDB6SU4WFL2QRAPBAWEE/action/storage_attestation","attest_author":"https://pith.science/pith/HBUSYITDB6SU4WFL2QRAPBAWEE/action/author_attestation","sign_citation":"https://pith.science/pith/HBUSYITDB6SU4WFL2QRAPBAWEE/action/citation_signature","submit_replication":"https://pith.science/pith/HBUSYITDB6SU4WFL2QRAPBAWEE/action/replication_record"}},"created_at":"2026-07-05T11:07:37.335104+00:00","updated_at":"2026-07-05T11:07:37.335104+00:00"}