{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:XIWANQMBJBYU25M27WBAXKK44R","short_pith_number":"pith:XIWANQMB","schema_version":"1.0","canonical_sha256":"ba2c06c18148714d759afd820ba95ce4745b557652157b4543f321c537b94fce","source":{"kind":"arxiv","id":"2202.05599","version":2},"attestation_state":"computed","paper":{"title":"ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Duo Zheng, Fandong Meng, Jiaan Wang, Jianfeng Qu, Jie Zhou, Zhixu Li, Ziyao Lu","submitted_at":"2022-02-11T13:32:14Z","abstract_excerpt":"We present ClidSum, a benchmark dataset for building cross-lingual summarization systems on dialogue documents. It consists of 67k+ dialogue documents from two subsets (i.e., SAMSum and MediaSum) and 112k+ annotated summaries in different target languages. Based on the proposed ClidSum, we introduce two benchmark settings for supervised and semi-supervised scenarios, respectively. We then build various baseline systems in different paradigms (pipeline and end-to-end) and conduct extensive experiments on ClidSum to provide deeper analyses. Furthermore, we propose mDialBART which extends mBART-5"},"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":"2202.05599","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-02-11T13:32:14Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e50fa7a0483d76b056e1b3526208c6e389f4a7d7651b836fe096276ddffe5b75","abstract_canon_sha256":"a1f3648ed7b4ab9873e44ed908c979f2cf1d595ece9c5392299903e2edf4d20d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:06:54.902462Z","signature_b64":"Ey2eqF56+9H7R4jCslnsEgnBidV1PnQP7VNOE9vP3jGJrlj4l9eqmMvup0GVP8whCgx4pX7NAS0MgkwVosHoBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba2c06c18148714d759afd820ba95ce4745b557652157b4543f321c537b94fce","last_reissued_at":"2026-07-05T05:06:54.901974Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:06:54.901974Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Duo Zheng, Fandong Meng, Jiaan Wang, Jianfeng Qu, Jie Zhou, Zhixu Li, Ziyao Lu","submitted_at":"2022-02-11T13:32:14Z","abstract_excerpt":"We present ClidSum, a benchmark dataset for building cross-lingual summarization systems on dialogue documents. It consists of 67k+ dialogue documents from two subsets (i.e., SAMSum and MediaSum) and 112k+ annotated summaries in different target languages. Based on the proposed ClidSum, we introduce two benchmark settings for supervised and semi-supervised scenarios, respectively. We then build various baseline systems in different paradigms (pipeline and end-to-end) and conduct extensive experiments on ClidSum to provide deeper analyses. Furthermore, we propose mDialBART which extends mBART-5"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.05599","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/2202.05599/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":"2202.05599","created_at":"2026-07-05T05:06:54.902030+00:00"},{"alias_kind":"arxiv_version","alias_value":"2202.05599v2","created_at":"2026-07-05T05:06:54.902030+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.05599","created_at":"2026-07-05T05:06:54.902030+00:00"},{"alias_kind":"pith_short_12","alias_value":"XIWANQMBJBYU","created_at":"2026-07-05T05:06:54.902030+00:00"},{"alias_kind":"pith_short_16","alias_value":"XIWANQMBJBYU25M2","created_at":"2026-07-05T05:06:54.902030+00:00"},{"alias_kind":"pith_short_8","alias_value":"XIWANQMB","created_at":"2026-07-05T05:06:54.902030+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/XIWANQMBJBYU25M27WBAXKK44R","json":"https://pith.science/pith/XIWANQMBJBYU25M27WBAXKK44R.json","graph_json":"https://pith.science/api/pith-number/XIWANQMBJBYU25M27WBAXKK44R/graph.json","events_json":"https://pith.science/api/pith-number/XIWANQMBJBYU25M27WBAXKK44R/events.json","paper":"https://pith.science/paper/XIWANQMB"},"agent_actions":{"view_html":"https://pith.science/pith/XIWANQMBJBYU25M27WBAXKK44R","download_json":"https://pith.science/pith/XIWANQMBJBYU25M27WBAXKK44R.json","view_paper":"https://pith.science/paper/XIWANQMB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2202.05599&json=true","fetch_graph":"https://pith.science/api/pith-number/XIWANQMBJBYU25M27WBAXKK44R/graph.json","fetch_events":"https://pith.science/api/pith-number/XIWANQMBJBYU25M27WBAXKK44R/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XIWANQMBJBYU25M27WBAXKK44R/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XIWANQMBJBYU25M27WBAXKK44R/action/storage_attestation","attest_author":"https://pith.science/pith/XIWANQMBJBYU25M27WBAXKK44R/action/author_attestation","sign_citation":"https://pith.science/pith/XIWANQMBJBYU25M27WBAXKK44R/action/citation_signature","submit_replication":"https://pith.science/pith/XIWANQMBJBYU25M27WBAXKK44R/action/replication_record"}},"created_at":"2026-07-05T05:06:54.902030+00:00","updated_at":"2026-07-05T05:06:54.902030+00:00"}