{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:DWAY4NKUKV7S7NMP2RFKP6S5F3","short_pith_number":"pith:DWAY4NKU","canonical_record":{"source":{"id":"2304.14402","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-27T17:58:49Z","cross_cats_sorted":[],"title_canon_sha256":"7b3df3d7c3b8f24859c0ab7a844b3e2e27d4e58c4443ab33e02389dd20025224","abstract_canon_sha256":"18661a9b5dd476bd613b984d4e5fac182c5f4c9080e87cbc744512c253d39955"},"schema_version":"1.0"},"canonical_sha256":"1d818e3554557f2fb58fd44aa7fa5d2ec3759e905e67a39920948e51bba3224b","source":{"kind":"arxiv","id":"2304.14402","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.14402","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"arxiv_version","alias_value":"2304.14402v3","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.14402","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"pith_short_12","alias_value":"DWAY4NKUKV7S","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"pith_short_16","alias_value":"DWAY4NKUKV7S7NMP","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"pith_short_8","alias_value":"DWAY4NKU","created_at":"2026-07-05T07:38:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:DWAY4NKUKV7S7NMP2RFKP6S5F3","target":"record","payload":{"canonical_record":{"source":{"id":"2304.14402","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-27T17:58:49Z","cross_cats_sorted":[],"title_canon_sha256":"7b3df3d7c3b8f24859c0ab7a844b3e2e27d4e58c4443ab33e02389dd20025224","abstract_canon_sha256":"18661a9b5dd476bd613b984d4e5fac182c5f4c9080e87cbc744512c253d39955"},"schema_version":"1.0"},"canonical_sha256":"1d818e3554557f2fb58fd44aa7fa5d2ec3759e905e67a39920948e51bba3224b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:38:27.156735Z","signature_b64":"7aIbwgNmQuyEYOlAhecSOP5On4XARHkmDu4caMbF3Sy3PdNXMsfMWvR3UTZYJ7sreSVzCWefTIcDDJZgtpDSDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1d818e3554557f2fb58fd44aa7fa5d2ec3759e905e67a39920948e51bba3224b","last_reissued_at":"2026-07-05T07:38:27.156273Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:38:27.156273Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.14402","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:38:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rDGovoObuKRKViQOF/TDbGNdxe8SecVtrmQ7Bs2D433f4EiTn0e2KPF1P4tJc8pQtdXsLddEW9or4zj66ex8DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T07:11:56.903892Z"},"content_sha256":"852fb46548f7bffeb15cfbcc7d9f0629295b17e20dcaaf83577317f6309ad8b0","schema_version":"1.0","event_id":"sha256:852fb46548f7bffeb15cfbcc7d9f0629295b17e20dcaaf83577317f6309ad8b0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:DWAY4NKUKV7S7NMP2RFKP6S5F3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Abdul Waheed, Alham Fikri Aji, Chiyu Zhang, Minghao Wu, Muhammad Abdul-Mageed","submitted_at":"2023-04-27T17:58:49Z","abstract_excerpt":"Large language models (LLMs) with instruction fine-tuning demonstrate superior generative capabilities. However, these models are resource-intensive. To alleviate this issue, we explore distilling knowledge from instruction-tuned LLMs into much smaller ones. To this end, we carefully develop a large set of 2.58M instructions based on both existing and newly-generated instructions. In addition to being sizable, we design our instructions to cover a broad set of topics to ensure diversity. Extensive analysis of our instruction dataset confirms its diversity, and we generate responses for these i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.14402","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2304.14402/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:38:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SHZNNktG2kHTkqgFNzfk7zoQmsF1ZGUL8Urne7/lSve9XDP5809iL/65FmikNzjZxkf93N/49MPwj7OrcvcqAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T07:11:56.904417Z"},"content_sha256":"fecf3b6a0830498b35f88598383c7fbdecac62978a6d3be16d00443de939ca87","schema_version":"1.0","event_id":"sha256:fecf3b6a0830498b35f88598383c7fbdecac62978a6d3be16d00443de939ca87"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DWAY4NKUKV7S7NMP2RFKP6S5F3/bundle.json","state_url":"https://pith.science/pith/DWAY4NKUKV7S7NMP2RFKP6S5F3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DWAY4NKUKV7S7NMP2RFKP6S5F3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T07:11:56Z","links":{"resolver":"https://pith.science/pith/DWAY4NKUKV7S7NMP2RFKP6S5F3","bundle":"https://pith.science/pith/DWAY4NKUKV7S7NMP2RFKP6S5F3/bundle.json","state":"https://pith.science/pith/DWAY4NKUKV7S7NMP2RFKP6S5F3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DWAY4NKUKV7S7NMP2RFKP6S5F3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:DWAY4NKUKV7S7NMP2RFKP6S5F3","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":"18661a9b5dd476bd613b984d4e5fac182c5f4c9080e87cbc744512c253d39955","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-27T17:58:49Z","title_canon_sha256":"7b3df3d7c3b8f24859c0ab7a844b3e2e27d4e58c4443ab33e02389dd20025224"},"schema_version":"1.0","source":{"id":"2304.14402","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.14402","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"arxiv_version","alias_value":"2304.14402v3","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.14402","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"pith_short_12","alias_value":"DWAY4NKUKV7S","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"pith_short_16","alias_value":"DWAY4NKUKV7S7NMP","created_at":"2026-07-05T07:38:27Z"},{"alias_kind":"pith_short_8","alias_value":"DWAY4NKU","created_at":"2026-07-05T07:38:27Z"}],"graph_snapshots":[{"event_id":"sha256:fecf3b6a0830498b35f88598383c7fbdecac62978a6d3be16d00443de939ca87","target":"graph","created_at":"2026-07-05T07:38:27Z","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/2304.14402/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) with instruction fine-tuning demonstrate superior generative capabilities. However, these models are resource-intensive. To alleviate this issue, we explore distilling knowledge from instruction-tuned LLMs into much smaller ones. To this end, we carefully develop a large set of 2.58M instructions based on both existing and newly-generated instructions. In addition to being sizable, we design our instructions to cover a broad set of topics to ensure diversity. Extensive analysis of our instruction dataset confirms its diversity, and we generate responses for these i","authors_text":"Abdul Waheed, Alham Fikri Aji, Chiyu Zhang, Minghao Wu, Muhammad Abdul-Mageed","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-27T17:58:49Z","title":"LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.14402","kind":"arxiv","version":3},"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":"sha256:852fb46548f7bffeb15cfbcc7d9f0629295b17e20dcaaf83577317f6309ad8b0","target":"record","created_at":"2026-07-05T07:38:27Z","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":"18661a9b5dd476bd613b984d4e5fac182c5f4c9080e87cbc744512c253d39955","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-27T17:58:49Z","title_canon_sha256":"7b3df3d7c3b8f24859c0ab7a844b3e2e27d4e58c4443ab33e02389dd20025224"},"schema_version":"1.0","source":{"id":"2304.14402","kind":"arxiv","version":3}},"canonical_sha256":"1d818e3554557f2fb58fd44aa7fa5d2ec3759e905e67a39920948e51bba3224b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1d818e3554557f2fb58fd44aa7fa5d2ec3759e905e67a39920948e51bba3224b","first_computed_at":"2026-07-05T07:38:27.156273Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:38:27.156273Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7aIbwgNmQuyEYOlAhecSOP5On4XARHkmDu4caMbF3Sy3PdNXMsfMWvR3UTZYJ7sreSVzCWefTIcDDJZgtpDSDg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:38:27.156735Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.14402","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:852fb46548f7bffeb15cfbcc7d9f0629295b17e20dcaaf83577317f6309ad8b0","sha256:fecf3b6a0830498b35f88598383c7fbdecac62978a6d3be16d00443de939ca87"],"state_sha256":"53f613d1301ffe6a274393ec5a06f0916906c2f8b8dcf15dc2ca171761086d6f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ojzd08gLMcpMfeAh/hIVv8P8yCrXWdIa5OtFS+CXR5LCxEuMFWIHdufE3BZZhSJF7el3LTcYvIzRuCmwHDX9BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T07:11:56.909492Z","bundle_sha256":"6a1f23b174fb78f1065afe3fdc79306d234d4640fb2ef379ab21b6488a1e95bb"}}