{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:QY6IOMJ5SFBTUZLOOT75TIAOD6","short_pith_number":"pith:QY6IOMJ5","schema_version":"1.0","canonical_sha256":"863c87313d91433a656e74ffd9a00e1f80b9625d19a7c84fdaab06b53319dbd0","source":{"kind":"arxiv","id":"2403.08943","version":1},"attestation_state":"computed","paper":{"title":"LMStyle Benchmark: Evaluating Text Style Transfer for Chatbots","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jianlin Chen","submitted_at":"2024-03-13T20:19:30Z","abstract_excerpt":"Since the breakthrough of ChatGPT, large language models (LLMs) have garnered significant attention in the research community. With the development of LLMs, the question of text style transfer for conversational models has emerged as a natural extension, where chatbots may possess their own styles or even characters. However, standard evaluation metrics have not yet been established for this new settings. This paper aims to address this issue by proposing the LMStyle Benchmark, a novel evaluation framework applicable to chat-style text style transfer (C-TST), that can measure the quality of st"},"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":"2403.08943","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-03-13T20:19:30Z","cross_cats_sorted":[],"title_canon_sha256":"86426d64fafe69b2e780df8957a85d6ad618190c54f8f3b89cbb956ea7a7a6cc","abstract_canon_sha256":"92234f1f9361a3f03140f0cc183eac848e9a96abc7d328939e2340d85a5fc696"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:55:49.508142Z","signature_b64":"JmQFeTY8WExQqb9VEcss3MeSERlfOaVXuCB+rEXe8Cs0iizKkPo6S1V1FRWG59mbOv+LqHU9Otf52HLbP3nnBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"863c87313d91433a656e74ffd9a00e1f80b9625d19a7c84fdaab06b53319dbd0","last_reissued_at":"2026-07-05T07:55:49.507623Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:55:49.507623Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LMStyle Benchmark: Evaluating Text Style Transfer for Chatbots","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jianlin Chen","submitted_at":"2024-03-13T20:19:30Z","abstract_excerpt":"Since the breakthrough of ChatGPT, large language models (LLMs) have garnered significant attention in the research community. With the development of LLMs, the question of text style transfer for conversational models has emerged as a natural extension, where chatbots may possess their own styles or even characters. However, standard evaluation metrics have not yet been established for this new settings. This paper aims to address this issue by proposing the LMStyle Benchmark, a novel evaluation framework applicable to chat-style text style transfer (C-TST), that can measure the quality of st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.08943","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/2403.08943/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":"2403.08943","created_at":"2026-07-05T07:55:49.507696+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.08943v1","created_at":"2026-07-05T07:55:49.507696+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.08943","created_at":"2026-07-05T07:55:49.507696+00:00"},{"alias_kind":"pith_short_12","alias_value":"QY6IOMJ5SFBT","created_at":"2026-07-05T07:55:49.507696+00:00"},{"alias_kind":"pith_short_16","alias_value":"QY6IOMJ5SFBTUZLO","created_at":"2026-07-05T07:55:49.507696+00:00"},{"alias_kind":"pith_short_8","alias_value":"QY6IOMJ5","created_at":"2026-07-05T07:55:49.507696+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2604.27365","citing_title":"From Notepad AI to Social Media: How Can Text Style Transformation Mitigate Social Harm?","ref_index":4,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QY6IOMJ5SFBTUZLOOT75TIAOD6","json":"https://pith.science/pith/QY6IOMJ5SFBTUZLOOT75TIAOD6.json","graph_json":"https://pith.science/api/pith-number/QY6IOMJ5SFBTUZLOOT75TIAOD6/graph.json","events_json":"https://pith.science/api/pith-number/QY6IOMJ5SFBTUZLOOT75TIAOD6/events.json","paper":"https://pith.science/paper/QY6IOMJ5"},"agent_actions":{"view_html":"https://pith.science/pith/QY6IOMJ5SFBTUZLOOT75TIAOD6","download_json":"https://pith.science/pith/QY6IOMJ5SFBTUZLOOT75TIAOD6.json","view_paper":"https://pith.science/paper/QY6IOMJ5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.08943&json=true","fetch_graph":"https://pith.science/api/pith-number/QY6IOMJ5SFBTUZLOOT75TIAOD6/graph.json","fetch_events":"https://pith.science/api/pith-number/QY6IOMJ5SFBTUZLOOT75TIAOD6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QY6IOMJ5SFBTUZLOOT75TIAOD6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QY6IOMJ5SFBTUZLOOT75TIAOD6/action/storage_attestation","attest_author":"https://pith.science/pith/QY6IOMJ5SFBTUZLOOT75TIAOD6/action/author_attestation","sign_citation":"https://pith.science/pith/QY6IOMJ5SFBTUZLOOT75TIAOD6/action/citation_signature","submit_replication":"https://pith.science/pith/QY6IOMJ5SFBTUZLOOT75TIAOD6/action/replication_record"}},"created_at":"2026-07-05T07:55:49.507696+00:00","updated_at":"2026-07-05T07:55:49.507696+00:00"}