{"id":"W4391335180","doi":"10.1145/3610977.3634999","title":"Generative Expressive Robot Behaviors using Large Language Models","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Multimodal Machine Learning Applications","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Robot; Human–computer interaction; Leverage (statistics); Motion (physics); Generative model; Generative grammar; Natural language; Context (archaeology); Artificial intelligence; Social robot; Mobile robot; Robot control","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":[0.0005654815,0.0009622648,0.0004640748,0.0003991587,0.0003813935,0.0009147885,0.001098817,0.0008856475,0.005343778],"category_scores_gemma":[0.002722764,0.0006405975,0.001229717,0.0002524208,0.0008789808,0.0009891952,0.001331735,0.001175033,0.001456396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007256393,"about_ca_system_score_gemma":0.0005799432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003582562,"about_ca_topic_score_gemma":0.008375501,"domain_scores_codex":[0.9995915,0.0001597804,0.00001736883,0.000127226,0.00007505273,0.00002899316],"domain_scores_gemma":[0.9990773,0.000656114,0.00005316706,0.0001108018,0.00006370356,0.000038917],"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":[0.0001302914,0.0001136129,0.001416027,0.0002191463,0.0000772664,0.0003712639,0.00071978,0.8658282,0.01428253,0.023137,0.004154562,0.08955048],"study_design_scores_gemma":[0.00001330572,0.00002137766,0.000113922,0.00001115243,0.000006816472,0.00003563071,0.0000367126,0.9858262,0.001461566,0.01076634,0.001697491,0.000009502633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02070966,0.00017885,0.9711851,0.0002407902,0.00003822086,0.00009985699,0.0003332203,0.003809313,0.003405003],"genre_scores_gemma":[0.6010007,0.0002534492,0.3859841,0.0002834438,0.00003992196,0.0006163047,0.001533168,0.001226709,0.009062151],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005343778,"threshold_uncertainty_score":0.01787668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03655862504537216,"score_gpt":0.3494611117712703,"score_spread":0.3129024867258982,"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."}}