{"id":"W4414939293","doi":"10.48550/arxiv.2505.09338","title":"Llama See, Llama Do: A Mechanistic Perspective on Contextual Entrainment and Distraction in LLMs","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Dispute Resolution and Class Actions","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto; University of Pennsylvania; Microsoft Research","keywords":"Entrainment (biomusicology); Distraction; Perspective (graphical); Context (archaeology); Set (abstract data type)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008120055,0.0005291041,0.0004484412,0.0003487324,0.0003511536,0.001177761,0.0006965008,0.0007152362,0.004203567],"category_scores_gemma":[0.008354265,0.0003667743,0.0004415163,0.0001906228,0.001034991,0.001352143,0.001857449,0.001116514,0.0004415812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005794311,"about_ca_system_score_gemma":0.0004111028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001054023,"about_ca_topic_score_gemma":0.0008951003,"domain_scores_codex":[0.9993713,0.0002095984,0.00003425197,0.0001419337,0.0001538363,0.00008906623],"domain_scores_gemma":[0.9974323,0.001503477,0.0003250932,0.0004178413,0.0001482158,0.0001729848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002051633,0.000327275,0.03780307,0.0008639603,0.0002147475,0.00231522,0.007724321,0.04483121,0.7827547,0.03434724,0.001608167,0.08515846],"study_design_scores_gemma":[0.0002413553,0.002356958,0.1468297,0.00035259,0.0003453613,0.002449684,0.004387286,0.3872043,0.315122,0.1236821,0.01664501,0.0003837035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8762667,0.0004773258,0.1114255,0.0007531709,0.00008414702,0.0001133357,0.000217848,0.001702204,0.008959766],"genre_scores_gemma":[0.9926058,0.00005397907,0.006437009,0.0001333019,0.00001272458,0.00004671972,0.00004900739,0.00008444694,0.0005770117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004203567,"threshold_uncertainty_score":0.01406229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0288819868834852,"score_gpt":0.2766045203722433,"score_spread":0.2477225334887581,"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."}}