{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GL4KQU53SSBGONXZ6TJQPARLZD","short_pith_number":"pith:GL4KQU53","canonical_record":{"source":{"id":"2408.01323","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-02T15:21:20Z","cross_cats_sorted":[],"title_canon_sha256":"ef9b20d783384f3c167a54a0d3a051209ff475fbcaf02d3a2c9e1c024f52032c","abstract_canon_sha256":"ab64307e94b774a27201899f487a69f5a8874b2ccc7ce861a487a9d9c4c9e13d"},"schema_version":"1.0"},"canonical_sha256":"32f8a853bb94826736f9f4d307822bc8f97c8482cbb35e02ae3accad324764e7","source":{"kind":"arxiv","id":"2408.01323","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.01323","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"arxiv_version","alias_value":"2408.01323v1","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.01323","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"pith_short_12","alias_value":"GL4KQU53SSBG","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"pith_short_16","alias_value":"GL4KQU53SSBGONXZ","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"pith_short_8","alias_value":"GL4KQU53","created_at":"2026-07-05T08:51:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GL4KQU53SSBGONXZ6TJQPARLZD","target":"record","payload":{"canonical_record":{"source":{"id":"2408.01323","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-02T15:21:20Z","cross_cats_sorted":[],"title_canon_sha256":"ef9b20d783384f3c167a54a0d3a051209ff475fbcaf02d3a2c9e1c024f52032c","abstract_canon_sha256":"ab64307e94b774a27201899f487a69f5a8874b2ccc7ce861a487a9d9c4c9e13d"},"schema_version":"1.0"},"canonical_sha256":"32f8a853bb94826736f9f4d307822bc8f97c8482cbb35e02ae3accad324764e7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:51:30.172780Z","signature_b64":"egW8FJH6lDbh9ejT/V8yUoA6QNxwRKJrBjVVJ6ldIazBn3wFS/8amqahjJ2IklTgUhvVgVTDJ4tq02BT0f9DCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"32f8a853bb94826736f9f4d307822bc8f97c8482cbb35e02ae3accad324764e7","last_reissued_at":"2026-07-05T08:51:30.172240Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:51:30.172240Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.01323","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:51:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E8migFjwtxorRWPQ/9EOCRocrxC/dc2zU4GYWCQo446x7ao8CvV6gfF+y9oPStLYB9vl4idyaVRvFk/TQLHjCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:34:13.686593Z"},"content_sha256":"227b9b573f4b5cdb9be10ed3d09fc6beac9b32c86bbd9c7da556943ffd852c74","schema_version":"1.0","event_id":"sha256:227b9b573f4b5cdb9be10ed3d09fc6beac9b32c86bbd9c7da556943ffd852c74"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GL4KQU53SSBGONXZ6TJQPARLZD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FANNO: Augmenting High-Quality Instruction Data with Open-Sourced LLMs Only","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Guanhua Chen, He Zhu, Junyou Su, Tianle Lun, Wenjia Zhang, Yicheng Tao, Zipei Fan","submitted_at":"2024-08-02T15:21:20Z","abstract_excerpt":"Instruction fine-tuning stands as a crucial advancement in leveraging large language models (LLMs) for enhanced task performance. However, the annotation of instruction datasets has traditionally been expensive and laborious, often relying on manual annotations or costly API calls of proprietary LLMs. To address these challenges, we introduce FANNO, a fully autonomous, open-sourced framework that revolutionizes the annotation process without the need for pre-existing annotated data. Utilizing a Mistral-7b-instruct model, FANNO efficiently produces diverse and high-quality datasets through a st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.01323","kind":"arxiv","version":1},"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/2408.01323/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":"2026-07-05T08:51:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kvgQvcFudooEQdSy+IVBxJ3Mclo8Lfbnoyqu6NDfpbf/Y5ydz43KvHos2kWaZyQUGHlZBWiqwS9ojvgvcBdWBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T10:34:13.687451Z"},"content_sha256":"9a032cc72c1a6fa5d6e2a40bff0f9b11aab45b8871faf0f36bc74e48ccac54d3","schema_version":"1.0","event_id":"sha256:9a032cc72c1a6fa5d6e2a40bff0f9b11aab45b8871faf0f36bc74e48ccac54d3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GL4KQU53SSBGONXZ6TJQPARLZD/bundle.json","state_url":"https://pith.science/pith/GL4KQU53SSBGONXZ6TJQPARLZD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GL4KQU53SSBGONXZ6TJQPARLZD/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":"2026-08-09T10:34:13Z","links":{"resolver":"https://pith.science/pith/GL4KQU53SSBGONXZ6TJQPARLZD","bundle":"https://pith.science/pith/GL4KQU53SSBGONXZ6TJQPARLZD/bundle.json","state":"https://pith.science/pith/GL4KQU53SSBGONXZ6TJQPARLZD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GL4KQU53SSBGONXZ6TJQPARLZD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GL4KQU53SSBGONXZ6TJQPARLZD","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":"ab64307e94b774a27201899f487a69f5a8874b2ccc7ce861a487a9d9c4c9e13d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-02T15:21:20Z","title_canon_sha256":"ef9b20d783384f3c167a54a0d3a051209ff475fbcaf02d3a2c9e1c024f52032c"},"schema_version":"1.0","source":{"id":"2408.01323","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.01323","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"arxiv_version","alias_value":"2408.01323v1","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.01323","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"pith_short_12","alias_value":"GL4KQU53SSBG","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"pith_short_16","alias_value":"GL4KQU53SSBGONXZ","created_at":"2026-07-05T08:51:30Z"},{"alias_kind":"pith_short_8","alias_value":"GL4KQU53","created_at":"2026-07-05T08:51:30Z"}],"graph_snapshots":[{"event_id":"sha256:9a032cc72c1a6fa5d6e2a40bff0f9b11aab45b8871faf0f36bc74e48ccac54d3","target":"graph","created_at":"2026-07-05T08:51:30Z","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/2408.01323/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Instruction fine-tuning stands as a crucial advancement in leveraging large language models (LLMs) for enhanced task performance. However, the annotation of instruction datasets has traditionally been expensive and laborious, often relying on manual annotations or costly API calls of proprietary LLMs. To address these challenges, we introduce FANNO, a fully autonomous, open-sourced framework that revolutionizes the annotation process without the need for pre-existing annotated data. Utilizing a Mistral-7b-instruct model, FANNO efficiently produces diverse and high-quality datasets through a st","authors_text":"Guanhua Chen, He Zhu, Junyou Su, Tianle Lun, Wenjia Zhang, Yicheng Tao, Zipei Fan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-02T15:21:20Z","title":"FANNO: Augmenting High-Quality Instruction Data with Open-Sourced LLMs Only"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.01323","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":"sha256:227b9b573f4b5cdb9be10ed3d09fc6beac9b32c86bbd9c7da556943ffd852c74","target":"record","created_at":"2026-07-05T08:51:30Z","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":"ab64307e94b774a27201899f487a69f5a8874b2ccc7ce861a487a9d9c4c9e13d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-02T15:21:20Z","title_canon_sha256":"ef9b20d783384f3c167a54a0d3a051209ff475fbcaf02d3a2c9e1c024f52032c"},"schema_version":"1.0","source":{"id":"2408.01323","kind":"arxiv","version":1}},"canonical_sha256":"32f8a853bb94826736f9f4d307822bc8f97c8482cbb35e02ae3accad324764e7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"32f8a853bb94826736f9f4d307822bc8f97c8482cbb35e02ae3accad324764e7","first_computed_at":"2026-07-05T08:51:30.172240Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:51:30.172240Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"egW8FJH6lDbh9ejT/V8yUoA6QNxwRKJrBjVVJ6ldIazBn3wFS/8amqahjJ2IklTgUhvVgVTDJ4tq02BT0f9DCw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:51:30.172780Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.01323","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:227b9b573f4b5cdb9be10ed3d09fc6beac9b32c86bbd9c7da556943ffd852c74","sha256:9a032cc72c1a6fa5d6e2a40bff0f9b11aab45b8871faf0f36bc74e48ccac54d3"],"state_sha256":"6df86be0a0bc3f708bef6ae92e0282382d86fb1a4de0d5ba14897624c7f4f7cc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4cLQET3Eoy0JSWttPQt7AISDgR3oZQWaywsNtpj9kKvGHjoVsPRaCh4yb839n1lQGICuEQSpH4XEWNgZovOADA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T10:34:13.694806Z","bundle_sha256":"08e4da862646f8509056e3a82d1c39387f591ed9c24592d67e26bf39ee74f513"}}