{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:65G444YZLSX6UGQQD6MIYKAB2Q","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":"3ebcef6f2a5e100b2e3630e0d6464f186566a513fcde2c59019611428080ff8d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-05-16T15:53:17Z","title_canon_sha256":"6c86428d1c2939ea26dd41d07ca742c1bbb51c750c017d73612c6fe587e1b8c3"},"schema_version":"1.0","source":{"id":"2105.07464","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.07464","created_at":"2026-07-05T03:10:39Z"},{"alias_kind":"arxiv_version","alias_value":"2105.07464v6","created_at":"2026-07-05T03:10:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.07464","created_at":"2026-07-05T03:10:39Z"},{"alias_kind":"pith_short_12","alias_value":"65G444YZLSX6","created_at":"2026-07-05T03:10:39Z"},{"alias_kind":"pith_short_16","alias_value":"65G444YZLSX6UGQQ","created_at":"2026-07-05T03:10:39Z"},{"alias_kind":"pith_short_8","alias_value":"65G444YZ","created_at":"2026-07-05T03:10:39Z"}],"graph_snapshots":[{"event_id":"sha256:f3c440f3708eececd187c442ec68f7f0c1e2ad3354a80e6778e4bab43e27bff0","target":"graph","created_at":"2026-07-05T03:10:39Z","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/2105.07464/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, considerable literature has grown up around the theme of few-shot named entity recognition (NER), but little published benchmark data specifically focused on the practical and challenging task. Current approaches collect existing supervised NER datasets and re-organize them to the few-shot setting for empirical study. These strategies conventionally aim to recognize coarse-grained entity types with few examples, while in practice, most unseen entity types are fine-grained. In this paper, we present Few-NERD, a large-scale human-annotated few-shot NER dataset with a hierarchy of 8 coa","authors_text":"Guangwei Xu, Hai-Tao Zheng, Ning Ding, Pengjun Xie, Xiaobin Wang, Xu Han, Yulin Chen, Zhiyuan Liu","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-05-16T15:53:17Z","title":"Few-NERD: A Few-Shot Named Entity Recognition Dataset"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.07464","kind":"arxiv","version":6},"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":"sha256:6208b25283d3630820d2e1473efe3fe14e46ad3385840dac3bed8deb8b643a48","target":"record","created_at":"2026-07-05T03:10:39Z","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":"3ebcef6f2a5e100b2e3630e0d6464f186566a513fcde2c59019611428080ff8d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-05-16T15:53:17Z","title_canon_sha256":"6c86428d1c2939ea26dd41d07ca742c1bbb51c750c017d73612c6fe587e1b8c3"},"schema_version":"1.0","source":{"id":"2105.07464","kind":"arxiv","version":6}},"canonical_sha256":"f74dce73195cafea1a101f988c2801d42098ba5d7dfc7c1141be5becc0576dd2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f74dce73195cafea1a101f988c2801d42098ba5d7dfc7c1141be5becc0576dd2","first_computed_at":"2026-07-05T03:10:39.876118Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:10:39.876118Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dcs48Ne8TcUkkr3m7jpLqwR/gZwjaOoLgNHOOxoODtUFlXkX25OKMJGS7ohp757Zq/s9FkZp3s/Kgf2+tTUaCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:10:39.876482Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.07464","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6208b25283d3630820d2e1473efe3fe14e46ad3385840dac3bed8deb8b643a48","sha256:f3c440f3708eececd187c442ec68f7f0c1e2ad3354a80e6778e4bab43e27bff0"],"state_sha256":"c2e6e4afaf1d1c8fe76cf78107cfee32135ae8a992aa8733a8e13b4cd6ddea52"}