{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:SMFQRV5XYFTKOI42PEZIG3YVGN","short_pith_number":"pith:SMFQRV5X","schema_version":"1.0","canonical_sha256":"930b08d7b7c166a7239a7932836f15334ff476bd7b807e7dac48e774a9d9dfa8","source":{"kind":"arxiv","id":"2406.06600","version":5},"attestation_state":"computed","paper":{"title":"HORAE: A Domain-Agnostic Language for Automated Service Regulation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.LG","authors_text":"He Li, Jianwei Yin, Jintao Chen, Kangjia Zhao, Liqiang Lu, Mingshuai Chen, Shuiguang Deng, Tiancheng Zhao, Xinkui Zhao, Yutao Sun, Zhongyi Wang","submitted_at":"2024-06-06T13:44:57Z","abstract_excerpt":"Artificial intelligence is rapidly encroaching on the field of service regulation. However, existing AI-based regulation techniques are often tailored to specific application domains and thus are difficult to generalize in an automated manner. This paper presents Horae, a unified specification language for modeling (multimodal) regulation rules across a diverse set of domains. We showcase how Horae facilitates an intelligent service regulation pipeline by further exploiting a fine-tuned large language model named RuleGPT that automates the Horae modeling process, thereby yielding an end-to-end"},"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":"2406.06600","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-06-06T13:44:57Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"c33b12d8ffc7673fdfc198b5ea3532b7fba2ea60d11b8c9d3898e5a5ac450015","abstract_canon_sha256":"c964e12d759ca3a543d240a15075dc3568efdf5162d04c70d17061e9d92e10a0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:00:37.569621Z","signature_b64":"ZKD15qQt/lZdnbrEWW+eWjFCiqaEIjrUggTjwsGedAPs8PmLnNRcykIcKrYvwh+i+va36VGMgdMhNBopVgfTDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"930b08d7b7c166a7239a7932836f15334ff476bd7b807e7dac48e774a9d9dfa8","last_reissued_at":"2026-07-05T11:00:37.569133Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:00:37.569133Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"HORAE: A Domain-Agnostic Language for Automated Service Regulation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.LG","authors_text":"He Li, Jianwei Yin, Jintao Chen, Kangjia Zhao, Liqiang Lu, Mingshuai Chen, Shuiguang Deng, Tiancheng Zhao, Xinkui Zhao, Yutao Sun, Zhongyi Wang","submitted_at":"2024-06-06T13:44:57Z","abstract_excerpt":"Artificial intelligence is rapidly encroaching on the field of service regulation. However, existing AI-based regulation techniques are often tailored to specific application domains and thus are difficult to generalize in an automated manner. This paper presents Horae, a unified specification language for modeling (multimodal) regulation rules across a diverse set of domains. We showcase how Horae facilitates an intelligent service regulation pipeline by further exploiting a fine-tuned large language model named RuleGPT that automates the Horae modeling process, thereby yielding an end-to-end"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.06600","kind":"arxiv","version":5},"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/2406.06600/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":"2406.06600","created_at":"2026-07-05T11:00:37.569190+00:00"},{"alias_kind":"arxiv_version","alias_value":"2406.06600v5","created_at":"2026-07-05T11:00:37.569190+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.06600","created_at":"2026-07-05T11:00:37.569190+00:00"},{"alias_kind":"pith_short_12","alias_value":"SMFQRV5XYFTK","created_at":"2026-07-05T11:00:37.569190+00:00"},{"alias_kind":"pith_short_16","alias_value":"SMFQRV5XYFTKOI42","created_at":"2026-07-05T11:00:37.569190+00:00"},{"alias_kind":"pith_short_8","alias_value":"SMFQRV5X","created_at":"2026-07-05T11:00:37.569190+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/SMFQRV5XYFTKOI42PEZIG3YVGN","json":"https://pith.science/pith/SMFQRV5XYFTKOI42PEZIG3YVGN.json","graph_json":"https://pith.science/api/pith-number/SMFQRV5XYFTKOI42PEZIG3YVGN/graph.json","events_json":"https://pith.science/api/pith-number/SMFQRV5XYFTKOI42PEZIG3YVGN/events.json","paper":"https://pith.science/paper/SMFQRV5X"},"agent_actions":{"view_html":"https://pith.science/pith/SMFQRV5XYFTKOI42PEZIG3YVGN","download_json":"https://pith.science/pith/SMFQRV5XYFTKOI42PEZIG3YVGN.json","view_paper":"https://pith.science/paper/SMFQRV5X","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2406.06600&json=true","fetch_graph":"https://pith.science/api/pith-number/SMFQRV5XYFTKOI42PEZIG3YVGN/graph.json","fetch_events":"https://pith.science/api/pith-number/SMFQRV5XYFTKOI42PEZIG3YVGN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SMFQRV5XYFTKOI42PEZIG3YVGN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SMFQRV5XYFTKOI42PEZIG3YVGN/action/storage_attestation","attest_author":"https://pith.science/pith/SMFQRV5XYFTKOI42PEZIG3YVGN/action/author_attestation","sign_citation":"https://pith.science/pith/SMFQRV5XYFTKOI42PEZIG3YVGN/action/citation_signature","submit_replication":"https://pith.science/pith/SMFQRV5XYFTKOI42PEZIG3YVGN/action/replication_record"}},"created_at":"2026-07-05T11:00:37.569190+00:00","updated_at":"2026-07-05T11:00:37.569190+00:00"}