{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:C3VURN3KYQYV4RIHPY7GQOPNJS","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":"67a8a4895d635cd50d72a252a2a7106fc587fcace830e2ac555ea4a44ee634b9","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-14T14:10:40Z","title_canon_sha256":"ee25c20575b1cf36e0a6c78d4fd41d4d69d0ae1d85e06f085364bccf42c8cdaa"},"schema_version":"1.0","source":{"id":"2311.08182","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.08182","created_at":"2026-07-05T07:12:41Z"},{"alias_kind":"arxiv_version","alias_value":"2311.08182v1","created_at":"2026-07-05T07:12:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.08182","created_at":"2026-07-05T07:12:41Z"},{"alias_kind":"pith_short_12","alias_value":"C3VURN3KYQYV","created_at":"2026-07-05T07:12:41Z"},{"alias_kind":"pith_short_16","alias_value":"C3VURN3KYQYV4RIH","created_at":"2026-07-05T07:12:41Z"},{"alias_kind":"pith_short_8","alias_value":"C3VURN3K","created_at":"2026-07-05T07:12:41Z"}],"graph_snapshots":[{"event_id":"sha256:f4047b9a27ccce6ea64269d0d497fe12d8a678dc73500b3115dcfadc8ad342cf","target":"graph","created_at":"2026-07-05T07:12:41Z","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/2311.08182/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Enhancing the instruction-following ability of Large Language Models (LLMs) primarily demands substantial instruction-tuning datasets. However, the sheer volume of these imposes a considerable computational burden and annotation cost. To investigate a label-efficient instruction tuning method that allows the model itself to actively sample subsets that are equally or even more effective, we introduce a self-evolving mechanism DiverseEvol. In this process, a model iteratively augments its training subset to refine its own performance, without requiring any intervention from humans or more advan","authors_text":"Benfeng Xu, Chang Zhou, Junyang Lin, Keming Lu, Qi Su, Shengguang Wu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-14T14:10:40Z","title":"Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.08182","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:ef5c79684bfe49236d80dcd53e53d00591f581b775db45bdc8806ad21e4b64de","target":"record","created_at":"2026-07-05T07:12:41Z","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":"67a8a4895d635cd50d72a252a2a7106fc587fcace830e2ac555ea4a44ee634b9","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-14T14:10:40Z","title_canon_sha256":"ee25c20575b1cf36e0a6c78d4fd41d4d69d0ae1d85e06f085364bccf42c8cdaa"},"schema_version":"1.0","source":{"id":"2311.08182","kind":"arxiv","version":1}},"canonical_sha256":"16eb48b76ac4315e45077e3e6839ed4ca46222bcd3dec54a052354650ba086ca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"16eb48b76ac4315e45077e3e6839ed4ca46222bcd3dec54a052354650ba086ca","first_computed_at":"2026-07-05T07:12:41.336060Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:12:41.336060Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TRVyjG7DupmAgrHR/ztB66IWuaSU+mmEyXhF7qzrebpdAE0Z1vRWo6npOkwfkFBczKoVjtEg/8HrhgfK17eJCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:12:41.336490Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.08182","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ef5c79684bfe49236d80dcd53e53d00591f581b775db45bdc8806ad21e4b64de","sha256:f4047b9a27ccce6ea64269d0d497fe12d8a678dc73500b3115dcfadc8ad342cf"],"state_sha256":"32a05fac23ae48f214803b63f59363d4659561aab9b1fdf6148573d1f38a8179"}