{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:6W5RSWS53G34LKV6SSRXVVB5TG","short_pith_number":"pith:6W5RSWS5","schema_version":"1.0","canonical_sha256":"f5bb195a5dd9b7c5aabe94a37ad43d99b36489fa6fe70072160fa92136933f16","source":{"kind":"arxiv","id":"2406.10590","version":2},"attestation_state":"computed","paper":{"title":"LLM-Mediated Domain-Specific Voice Agents: The Case of TextileBot","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Elia Gatti, James Hardwick, Marianna Obrist, Miriam Ribul, Shu Zhong, Youngjun Cho","submitted_at":"2024-06-15T10:42:39Z","abstract_excerpt":"Developing domain-specific conversational agents (CAs) has been challenged by the need for extensive domain-focused data. Recent advancements in Large Language Models (LLMs) make them a viable option as a knowledge backbone. LLMs behaviour can be enhanced through prompting, instructing them to perform downstream tasks in a zero-shot fashion (i.e. without training). To this end, we incorporated structural knowledge into prompts and used prompted LLMs to prototyping domain-specific CAs. We demonstrate a case study in a specific domain-textile circularity - TextileBot, we present the design, deve"},"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":"2406.10590","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2024-06-15T10:42:39Z","cross_cats_sorted":[],"title_canon_sha256":"be1392591dc6d9f99830ff2bab9d27e647d80ac9f556980e65a9d33abc0fd8b0","abstract_canon_sha256":"211052ef31a08139fb53975d7f4d2435612996b44a422484c5af8c7576621015"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:09:05.274134Z","signature_b64":"ra1Xw/Kcyt+1cCzYkDl6s3ar9GggVweJiaqLtcLMb/QnA1xeXlc9og+GsWgZiPBmRv/LUcIITHkE3wy+r+3UDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f5bb195a5dd9b7c5aabe94a37ad43d99b36489fa6fe70072160fa92136933f16","last_reissued_at":"2026-07-05T10:09:05.273613Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:09:05.273613Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LLM-Mediated Domain-Specific Voice Agents: The Case of TextileBot","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Elia Gatti, James Hardwick, Marianna Obrist, Miriam Ribul, Shu Zhong, Youngjun Cho","submitted_at":"2024-06-15T10:42:39Z","abstract_excerpt":"Developing domain-specific conversational agents (CAs) has been challenged by the need for extensive domain-focused data. Recent advancements in Large Language Models (LLMs) make them a viable option as a knowledge backbone. LLMs behaviour can be enhanced through prompting, instructing them to perform downstream tasks in a zero-shot fashion (i.e. without training). To this end, we incorporated structural knowledge into prompts and used prompted LLMs to prototyping domain-specific CAs. We demonstrate a case study in a specific domain-textile circularity - TextileBot, we present the design, deve"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.10590","kind":"arxiv","version":2},"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/2406.10590/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":"2406.10590","created_at":"2026-07-05T10:09:05.273683+00:00"},{"alias_kind":"arxiv_version","alias_value":"2406.10590v2","created_at":"2026-07-05T10:09:05.273683+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.10590","created_at":"2026-07-05T10:09:05.273683+00:00"},{"alias_kind":"pith_short_12","alias_value":"6W5RSWS53G34","created_at":"2026-07-05T10:09:05.273683+00:00"},{"alias_kind":"pith_short_16","alias_value":"6W5RSWS53G34LKV6","created_at":"2026-07-05T10:09:05.273683+00:00"},{"alias_kind":"pith_short_8","alias_value":"6W5RSWS5","created_at":"2026-07-05T10:09:05.273683+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/6W5RSWS53G34LKV6SSRXVVB5TG","json":"https://pith.science/pith/6W5RSWS53G34LKV6SSRXVVB5TG.json","graph_json":"https://pith.science/api/pith-number/6W5RSWS53G34LKV6SSRXVVB5TG/graph.json","events_json":"https://pith.science/api/pith-number/6W5RSWS53G34LKV6SSRXVVB5TG/events.json","paper":"https://pith.science/paper/6W5RSWS5"},"agent_actions":{"view_html":"https://pith.science/pith/6W5RSWS53G34LKV6SSRXVVB5TG","download_json":"https://pith.science/pith/6W5RSWS53G34LKV6SSRXVVB5TG.json","view_paper":"https://pith.science/paper/6W5RSWS5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2406.10590&json=true","fetch_graph":"https://pith.science/api/pith-number/6W5RSWS53G34LKV6SSRXVVB5TG/graph.json","fetch_events":"https://pith.science/api/pith-number/6W5RSWS53G34LKV6SSRXVVB5TG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6W5RSWS53G34LKV6SSRXVVB5TG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6W5RSWS53G34LKV6SSRXVVB5TG/action/storage_attestation","attest_author":"https://pith.science/pith/6W5RSWS53G34LKV6SSRXVVB5TG/action/author_attestation","sign_citation":"https://pith.science/pith/6W5RSWS53G34LKV6SSRXVVB5TG/action/citation_signature","submit_replication":"https://pith.science/pith/6W5RSWS53G34LKV6SSRXVVB5TG/action/replication_record"}},"created_at":"2026-07-05T10:09:05.273683+00:00","updated_at":"2026-07-05T10:09:05.273683+00:00"}