{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:437CQS27UKPFZBP6CL5EN5NAXT","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":"473dbefe78a3359a326f11d846c322e81c701acd2a0e61cbe53fe03cd3e8c588","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-08-30T19:18:24Z","title_canon_sha256":"47cdeb28952efc8f094f3c301d6a2a877892d1b60c1e5fa0347e2a2966725b48"},"schema_version":"1.0","source":{"id":"2108.13487","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.13487","created_at":"2026-07-05T03:10:14Z"},{"alias_kind":"arxiv_version","alias_value":"2108.13487v1","created_at":"2026-07-05T03:10:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.13487","created_at":"2026-07-05T03:10:14Z"},{"alias_kind":"pith_short_12","alias_value":"437CQS27UKPF","created_at":"2026-07-05T03:10:14Z"},{"alias_kind":"pith_short_16","alias_value":"437CQS27UKPFZBP6","created_at":"2026-07-05T03:10:14Z"},{"alias_kind":"pith_short_8","alias_value":"437CQS27","created_at":"2026-07-05T03:10:14Z"}],"graph_snapshots":[{"event_id":"sha256:ec94a272fc184d34c35e8123ba552837c2fe3f5425f1c83f8c6f1e5518baf916","target":"graph","created_at":"2026-07-05T03:10:14Z","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/2108.13487/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data annotation is a time-consuming and labor-intensive process for many NLP tasks. Although there exist various methods to produce pseudo data labels, they are often task-specific and require a decent amount of labeled data to start with. Recently, the immense language model GPT-3 with 175 billion parameters has achieved tremendous improvement across many few-shot learning tasks. In this paper, we explore ways to leverage GPT-3 as a low-cost data labeler to train other models. We find that, to make the downstream model achieve the same performance on a variety of NLU and NLG tasks, it costs 5","authors_text":"Chenguang Zhu, Michael Zeng, Shuohang Wang, Yang Liu, Yichong Xu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-08-30T19:18:24Z","title":"Want To Reduce Labeling Cost? GPT-3 Can Help"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.13487","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:dcba12e91fd585872917c90e31cb6e717d157e7a3df36ef93ed1fb1fa79c7831","target":"record","created_at":"2026-07-05T03:10:14Z","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":"473dbefe78a3359a326f11d846c322e81c701acd2a0e61cbe53fe03cd3e8c588","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-08-30T19:18:24Z","title_canon_sha256":"47cdeb28952efc8f094f3c301d6a2a877892d1b60c1e5fa0347e2a2966725b48"},"schema_version":"1.0","source":{"id":"2108.13487","kind":"arxiv","version":1}},"canonical_sha256":"e6fe284b5fa29e5c85fe12fa46f5a0bcd78d5f6c2daa5dbff00dca8af435b8d6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e6fe284b5fa29e5c85fe12fa46f5a0bcd78d5f6c2daa5dbff00dca8af435b8d6","first_computed_at":"2026-07-05T03:10:14.687070Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:10:14.687070Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Kak8+6vOG0fp9OJcaI1EUvX01DViqF1Ea/YLRFl6rhNsvNp6xHH1Gfe2XWJTMexPPlJ5bYToZootYM5+TsjEDg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:10:14.687572Z","signed_message":"canonical_sha256_bytes"},"source_id":"2108.13487","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dcba12e91fd585872917c90e31cb6e717d157e7a3df36ef93ed1fb1fa79c7831","sha256:ec94a272fc184d34c35e8123ba552837c2fe3f5425f1c83f8c6f1e5518baf916"],"state_sha256":"053d975c9edf6e7fbeafc21253998c10d0fe5fb5bf8d76284270a53f34b46f9e"}