{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:RMAXJG4OGCHXFGFMW2DP4XAEOW","short_pith_number":"pith:RMAXJG4O","schema_version":"1.0","canonical_sha256":"8b01749b8e308f7298acb686fe5c04759bb5d6d12aa9935ccda7487886676039","source":{"kind":"arxiv","id":"2102.04506","version":1},"attestation_state":"computed","paper":{"title":"A Hybrid Task-Oriented Dialog System with Domain and Task Adaptive Pretraining","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Boliang Zhang, Kevin Knight, Kun Han, Ning Ding, Tianhao Shen, Ying Lyu, Zhaoyang Jia","submitted_at":"2021-02-08T20:02:30Z","abstract_excerpt":"This paper describes our submission for the End-to-end Multi-domain Task Completion Dialog shared task at the 9th Dialog System Technology Challenge (DSTC-9). Participants in the shared task build an end-to-end task completion dialog system which is evaluated by human evaluation and a user simulator based automatic evaluation. Different from traditional pipelined approaches where modules are optimized individually and suffer from cascading failure, we propose an end-to-end dialog system that 1) uses Generative Pretraining 2 (GPT-2) as the backbone to jointly solve Natural Language Understandin"},"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":"2102.04506","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-02-08T20:02:30Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d28703d77b0e5f1188427b2feb669f2c8259e8e077788576cd4cf7f41ba88230","abstract_canon_sha256":"02f2c468f6d0669719e8cd7af907b2c5a606669e6de67d2e028ae0364db6a9cc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:13:34.691382Z","signature_b64":"SJ0WK4544nv7V3o8ggltKcKhUhUFx5LI7aERNidGzFtOAey2Co7fIjh9B7d+YXOlIHBG6SSwKRUkA9tSg3TtAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8b01749b8e308f7298acb686fe5c04759bb5d6d12aa9935ccda7487886676039","last_reissued_at":"2026-07-05T02:13:34.690968Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:13:34.690968Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Hybrid Task-Oriented Dialog System with Domain and Task Adaptive Pretraining","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Boliang Zhang, Kevin Knight, Kun Han, Ning Ding, Tianhao Shen, Ying Lyu, Zhaoyang Jia","submitted_at":"2021-02-08T20:02:30Z","abstract_excerpt":"This paper describes our submission for the End-to-end Multi-domain Task Completion Dialog shared task at the 9th Dialog System Technology Challenge (DSTC-9). Participants in the shared task build an end-to-end task completion dialog system which is evaluated by human evaluation and a user simulator based automatic evaluation. Different from traditional pipelined approaches where modules are optimized individually and suffer from cascading failure, we propose an end-to-end dialog system that 1) uses Generative Pretraining 2 (GPT-2) as the backbone to jointly solve Natural Language Understandin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.04506","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/2102.04506/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":"2102.04506","created_at":"2026-07-05T02:13:34.691023+00:00"},{"alias_kind":"arxiv_version","alias_value":"2102.04506v1","created_at":"2026-07-05T02:13:34.691023+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.04506","created_at":"2026-07-05T02:13:34.691023+00:00"},{"alias_kind":"pith_short_12","alias_value":"RMAXJG4OGCHX","created_at":"2026-07-05T02:13:34.691023+00:00"},{"alias_kind":"pith_short_16","alias_value":"RMAXJG4OGCHXFGFM","created_at":"2026-07-05T02:13:34.691023+00:00"},{"alias_kind":"pith_short_8","alias_value":"RMAXJG4O","created_at":"2026-07-05T02:13:34.691023+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/RMAXJG4OGCHXFGFMW2DP4XAEOW","json":"https://pith.science/pith/RMAXJG4OGCHXFGFMW2DP4XAEOW.json","graph_json":"https://pith.science/api/pith-number/RMAXJG4OGCHXFGFMW2DP4XAEOW/graph.json","events_json":"https://pith.science/api/pith-number/RMAXJG4OGCHXFGFMW2DP4XAEOW/events.json","paper":"https://pith.science/paper/RMAXJG4O"},"agent_actions":{"view_html":"https://pith.science/pith/RMAXJG4OGCHXFGFMW2DP4XAEOW","download_json":"https://pith.science/pith/RMAXJG4OGCHXFGFMW2DP4XAEOW.json","view_paper":"https://pith.science/paper/RMAXJG4O","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2102.04506&json=true","fetch_graph":"https://pith.science/api/pith-number/RMAXJG4OGCHXFGFMW2DP4XAEOW/graph.json","fetch_events":"https://pith.science/api/pith-number/RMAXJG4OGCHXFGFMW2DP4XAEOW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RMAXJG4OGCHXFGFMW2DP4XAEOW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RMAXJG4OGCHXFGFMW2DP4XAEOW/action/storage_attestation","attest_author":"https://pith.science/pith/RMAXJG4OGCHXFGFMW2DP4XAEOW/action/author_attestation","sign_citation":"https://pith.science/pith/RMAXJG4OGCHXFGFMW2DP4XAEOW/action/citation_signature","submit_replication":"https://pith.science/pith/RMAXJG4OGCHXFGFMW2DP4XAEOW/action/replication_record"}},"created_at":"2026-07-05T02:13:34.691023+00:00","updated_at":"2026-07-05T02:13:34.691023+00:00"}