{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ASLRKP46QAH6LI3WM35NYPUSTP","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"e54edeb0c50e778e9af4c1e3bab2b92c742ed31ffb104cf8196510e74d48d990","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-10-09T18:34:17Z","title_canon_sha256":"567e84da120b0558e72215b5a78866324649ba35487a0557986606f463252ae5"},"schema_version":"1.0","source":{"id":"1910.04196","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.04196","created_at":"2026-07-05T00:11:05Z"},{"alias_kind":"arxiv_version","alias_value":"1910.04196v1","created_at":"2026-07-05T00:11:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.04196","created_at":"2026-07-05T00:11:05Z"},{"alias_kind":"pith_short_12","alias_value":"ASLRKP46QAH6","created_at":"2026-07-05T00:11:05Z"},{"alias_kind":"pith_short_16","alias_value":"ASLRKP46QAH6LI3W","created_at":"2026-07-05T00:11:05Z"},{"alias_kind":"pith_short_8","alias_value":"ASLRKP46","created_at":"2026-07-05T00:11:05Z"}],"graph_snapshots":[{"event_id":"sha256:6a335884a60147131f8917db8a45a48164a9f0c59b230e84f02447b755df8958","target":"graph","created_at":"2026-07-05T00:11:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1910.04196/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Expanding new functionalities efficiently is an ongoing challenge for single-turn task-oriented dialogue systems. In this work, we explore functionality-specific semi-supervised learning via self-training. We consider methods that augment training data automatically from unlabeled data sets in a functionality-targeted manner. In addition, we examine multiple techniques for efficient selection of augmented utterances to reduce training time and increase diversity. First, we consider paraphrase detection methods that attempt to find utterance variants of labeled training data with good coverage.","authors_text":"Eunah Cho, He Xie, John P. Lalor, Varun Kumar, William M. Campbell","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-10-09T18:34:17Z","title":"Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.04196","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:59dd56f02c3dd6b00c98317599097e5892984e75ee83ca3ddfdad734ec269a3e","target":"record","created_at":"2026-07-05T00:11:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"e54edeb0c50e778e9af4c1e3bab2b92c742ed31ffb104cf8196510e74d48d990","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-10-09T18:34:17Z","title_canon_sha256":"567e84da120b0558e72215b5a78866324649ba35487a0557986606f463252ae5"},"schema_version":"1.0","source":{"id":"1910.04196","kind":"arxiv","version":1}},"canonical_sha256":"0497153f9e800fe5a37666fadc3e929bca76b352b6a8493088b5bdd94d8d2251","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0497153f9e800fe5a37666fadc3e929bca76b352b6a8493088b5bdd94d8d2251","first_computed_at":"2026-07-05T00:11:05.809612Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:11:05.809612Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ugGN0Urp+l/5+uszPQRT5BkV1hbgrYsJsnqUNvmW2ofIyiU+gYkSMgIvS8pHA/bMbocGlB8Uou4C33YjhA9uAA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:11:05.809997Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.04196","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:59dd56f02c3dd6b00c98317599097e5892984e75ee83ca3ddfdad734ec269a3e","sha256:6a335884a60147131f8917db8a45a48164a9f0c59b230e84f02447b755df8958"],"state_sha256":"b8df0e0701b1ae7be11c1693cbc9b9b2e6a409af8878b5881cd5c350f64507bc"}