{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:2UCQKGWTC46NAUJYWIRFOMH3FU","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":"0b4e4d50fce056d3b7ef828e06da038e97243f831778c027e6ee223e31afdf03","cross_cats_sorted":["cs.AI","cs.DC","cs.LG","cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-07T11:19:30Z","title_canon_sha256":"778144e6c85bc27302f3210e166ae4761b76a82ebd4604694e6032ee18ac828a"},"schema_version":"1.0","source":{"id":"2406.04845","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04845","created_at":"2026-07-05T08:28:49Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04845v1","created_at":"2026-07-05T08:28:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04845","created_at":"2026-07-05T08:28:49Z"},{"alias_kind":"pith_short_12","alias_value":"2UCQKGWTC46N","created_at":"2026-07-05T08:28:49Z"},{"alias_kind":"pith_short_16","alias_value":"2UCQKGWTC46NAUJY","created_at":"2026-07-05T08:28:49Z"},{"alias_kind":"pith_short_8","alias_value":"2UCQKGWT","created_at":"2026-07-05T08:28:49Z"}],"graph_snapshots":[{"event_id":"sha256:b9aa220f40195fc18066590341ff4e44d3b3dd685093e9f3eb34d11772cc1fc2","target":"graph","created_at":"2026-07-05T08:28:49Z","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/2406.04845/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning has enabled multiple parties to collaboratively train large language models without directly sharing their data (FedLLM). Following this training paradigm, the community has put massive efforts from diverse aspects including framework, performance, and privacy. However, an unpleasant fact is that there are currently no realistic datasets and benchmarks for FedLLM and previous works all rely on artificially constructed datasets, failing to capture properties in real-world scenarios. Addressing this, we propose FedLLM-Bench, which involves 8 training methods, 4 training datase","authors_text":"Jingyi Chai, Rui Ge, Rui Ye, Siheng Chen, Xinyu Zhu, Yanfeng Wang, Yang Liu, Yaxin Du","cross_cats":["cs.AI","cs.DC","cs.LG","cs.MA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-07T11:19:30Z","title":"FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04845","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:e78ffb717c9c3b36ac499ad42616b542ffa059bf7a8568b73cb618387153e294","target":"record","created_at":"2026-07-05T08:28:49Z","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":"0b4e4d50fce056d3b7ef828e06da038e97243f831778c027e6ee223e31afdf03","cross_cats_sorted":["cs.AI","cs.DC","cs.LG","cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-07T11:19:30Z","title_canon_sha256":"778144e6c85bc27302f3210e166ae4761b76a82ebd4604694e6032ee18ac828a"},"schema_version":"1.0","source":{"id":"2406.04845","kind":"arxiv","version":1}},"canonical_sha256":"d505051ad3173cd05138b2225730fb2d049c0ad2c89393218076d0395ba56917","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d505051ad3173cd05138b2225730fb2d049c0ad2c89393218076d0395ba56917","first_computed_at":"2026-07-05T08:28:49.911754Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:28:49.911754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hDeZ7DSW0ral5fUZcjswlS57114vWlMvtn1ZFqDFXJg7ePb0ROidJoz3VdBxnzMSrzdFX5j3GwSETa0lY4fRBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:28:49.912166Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.04845","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e78ffb717c9c3b36ac499ad42616b542ffa059bf7a8568b73cb618387153e294","sha256:b9aa220f40195fc18066590341ff4e44d3b3dd685093e9f3eb34d11772cc1fc2"],"state_sha256":"e6813adaca4cd1590364026e6e4200b5a4861fca1b426471e932c735ed614adf"}