{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:4LVJREPZHGEIJR4E6JUXDL64C5","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":"c768760ccd9a38b8c71839e99a377fcb5f5f72d4a77aded3bdf73a8e66fb502b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-08-07T03:39:52Z","title_canon_sha256":"3b7897fa8319c7fc973e6c395b515b1fe26c5619e00d0774f44cf8a011a9e1d7"},"schema_version":"1.0","source":{"id":"2308.03279","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.03279","created_at":"2026-07-05T07:35:20Z"},{"alias_kind":"arxiv_version","alias_value":"2308.03279v2","created_at":"2026-07-05T07:35:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.03279","created_at":"2026-07-05T07:35:20Z"},{"alias_kind":"pith_short_12","alias_value":"4LVJREPZHGEI","created_at":"2026-07-05T07:35:20Z"},{"alias_kind":"pith_short_16","alias_value":"4LVJREPZHGEIJR4E","created_at":"2026-07-05T07:35:20Z"},{"alias_kind":"pith_short_8","alias_value":"4LVJREPZ","created_at":"2026-07-05T07:35:20Z"}],"graph_snapshots":[{"event_id":"sha256:c90182175105eec0171e757333b6baee01c15df547b266391df4dfd6ba83e0d6","target":"graph","created_at":"2026-07-05T07:35:20Z","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/2308.03279/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have demonstrated remarkable generalizability, such as understanding arbitrary entities and relations. Instruction tuning has proven effective for distilling LLMs into more cost-efficient models such as Alpaca and Vicuna. Yet such student models still trail the original LLMs by large margins in downstream applications. In this paper, we explore targeted distillation with mission-focused instruction tuning to train student models that can excel in a broad application class such as open information extraction. Using named entity recognition (NER) for case study, we s","authors_text":"Hoifung Poon, Muhao Chen, Sheng Zhang, Wenxuan Zhou, Yu Gu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-08-07T03:39:52Z","title":"UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.03279","kind":"arxiv","version":2},"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":"sha256:0c35de7d7cce59edbdd4606c86cc85cde71fa36a277224dd8e59523a57ad413b","target":"record","created_at":"2026-07-05T07:35:20Z","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":"c768760ccd9a38b8c71839e99a377fcb5f5f72d4a77aded3bdf73a8e66fb502b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-08-07T03:39:52Z","title_canon_sha256":"3b7897fa8319c7fc973e6c395b515b1fe26c5619e00d0774f44cf8a011a9e1d7"},"schema_version":"1.0","source":{"id":"2308.03279","kind":"arxiv","version":2}},"canonical_sha256":"e2ea9891f9398884c784f26971afdc174d163474cdb5c835f88ac57dd47e2273","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e2ea9891f9398884c784f26971afdc174d163474cdb5c835f88ac57dd47e2273","first_computed_at":"2026-07-05T07:35:20.205491Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:35:20.205491Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zkJpeBzjEDHhInvwR7tPEgyAVXAMz+5RMk2WNizp/E+AsC86klzLQ8XopoYaTHyNNPR4LnwDC8//oiJ4/XR9BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:35:20.205925Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.03279","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0c35de7d7cce59edbdd4606c86cc85cde71fa36a277224dd8e59523a57ad413b","sha256:c90182175105eec0171e757333b6baee01c15df547b266391df4dfd6ba83e0d6"],"state_sha256":"756efbfe9ca3f2877129a885b4477349cb05436979ee77638099775313cbf3ba"}