{"id":"W4404673562","doi":"10.1007/978-3-031-73024-5_4","title":"Modality Translation for Object Detection Adaptation Without Forgetting Prior Knowledge","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Forgetting; Modality (human–computer interaction); Adaptation (eye); Translation (biology); Artificial intelligence; Object (grammar); Computer vision; Natural language processing; Cognitive psychology; Neuroscience; Psychology","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":[0.0008165027,0.001031608,0.001078989,0.0006896309,0.0003674527,0.0007536505,0.001552887,0.001362344,0.009123525],"category_scores_gemma":[0.001742072,0.0004130073,0.001310548,0.0008428146,0.0005593062,0.001683709,0.001813729,0.001960933,0.005821993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003164306,"about_ca_system_score_gemma":0.0004291334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001411709,"about_ca_topic_score_gemma":0.00187884,"domain_scores_codex":[0.999508,0.0000895128,0.00002115981,0.0002208455,0.0001082955,0.0000520612],"domain_scores_gemma":[0.9994516,0.0001980362,0.00001739999,0.0001935044,0.0001101716,0.00002925288],"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":[0.0002814658,0.0001766666,0.0002671328,0.000236576,0.0001349175,0.0001693408,0.00009252327,0.01765279,0.07528596,0.00639309,0.01104784,0.8882617],"study_design_scores_gemma":[0.00003818331,0.0002332415,0.001549541,0.0000576105,0.0001855466,0.0008773965,0.00007445923,0.8283004,0.09992912,0.04741041,0.02126731,0.00007673327],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00463172,0.0006351242,0.9887311,0.0000796042,0.0001961808,0.0000455613,0.0001726928,0.002920177,0.002587891],"genre_scores_gemma":[0.2193916,0.001743029,0.7507781,0.0007467794,0.0003811678,0.0003017973,0.001981287,0.001285999,0.02339016],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009123525,"threshold_uncertainty_score":0.03052127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03939968520406524,"score_gpt":0.289039440942685,"score_spread":0.2496397557386198,"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."}}