{"id":"W4401508395","doi":"10.1109/infocom52122.2024.10621164","title":"Titanic: Towards Production Federated Learning with Large Language Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Production (economics); Natural language processing; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004236084,0.001612855,0.001445924,0.0007614724,0.0009783873,0.002227969,0.004524407,0.002154872,0.003083982],"category_scores_gemma":[0.01645956,0.0009331582,0.001257295,0.001102629,0.001604055,0.006448328,0.005245861,0.004323007,0.00201247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001683953,"about_ca_system_score_gemma":0.002743192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005521855,"about_ca_topic_score_gemma":0.007801355,"domain_scores_codex":[0.9962206,0.001463306,0.0001774573,0.001077325,0.0007529091,0.0003084266],"domain_scores_gemma":[0.9924131,0.003466477,0.0002745364,0.002888261,0.0006651994,0.000292352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001238027,0.0009057146,0.003300507,0.0002966042,0.0002609497,0.00042336,0.0004851093,0.6207298,0.01310797,0.02384853,0.02205641,0.313347],"study_design_scores_gemma":[0.00003280735,0.00003779778,0.00006396667,0.000005381417,0.000007377992,0.0000297065,0.00003226781,0.9830404,0.002102883,0.01359185,0.001047225,0.000008279982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02451298,0.0002898505,0.9531797,0.0006031529,0.00008264255,0.000134266,0.0003206602,0.01938921,0.001487583],"genre_scores_gemma":[0.4730191,0.0002173402,0.5175897,0.001108468,0.00009038096,0.0004041159,0.002587239,0.001512064,0.00347158],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005521855,"threshold_uncertainty_score":0.02240282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02488295360538529,"score_gpt":0.2738356930595304,"score_spread":0.2489527394541451,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}