{"id":"W4404782654","doi":"10.18653/v1/2024.emnlp-main.382","title":"MirrorStories: Reflecting Diversity through Personalized Narrative Generation with Large Language Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Narrative; Diversity (politics); Computer science; Natural language generation; Natural language processing; Linguistics; Sociology; Natural language; Anthropology; Philosophy","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005141543,0.001203491,0.0004879216,0.001083634,0.0005789812,0.002371224,0.001540475,0.001053903,0.004592804],"category_scores_gemma":[0.02487581,0.000472601,0.0007697641,0.0005710302,0.0007484219,0.00400323,0.002745907,0.001220481,0.001723277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006774053,"about_ca_system_score_gemma":0.00068915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001429424,"about_ca_topic_score_gemma":0.003642192,"domain_scores_codex":[0.9960405,0.002907685,0.0001371088,0.0004798937,0.000361791,0.00007306971],"domain_scores_gemma":[0.9854989,0.0111741,0.0006088218,0.001872615,0.000615606,0.0002300146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001825194,0.0008494801,0.0190001,0.002286941,0.0005171448,0.001195367,0.02128681,0.1056566,0.04311622,0.0234712,0.03884435,0.7419506],"study_design_scores_gemma":[0.0003194993,0.0006746387,0.004964194,0.0002653582,0.0002398076,0.0009362658,0.005448091,0.8417237,0.03900497,0.03132729,0.07489292,0.0002032782],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3366444,0.001621199,0.6260496,0.00177143,0.0003059554,0.001119434,0.003551732,0.01721416,0.01172209],"genre_scores_gemma":[0.6026342,0.0003437367,0.3856315,0.0003294803,0.00009552445,0.0007149004,0.005378526,0.0008428014,0.0040293],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005141543,"threshold_uncertainty_score":0.0271914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0900600388191288,"score_gpt":0.3256336003900595,"score_spread":0.2355735615709307,"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."}}