{"id":"W4386249616","doi":"10.1109/crv60082.2023.00046","title":"Gradient-Based Maximally Interfered Retrieval for Domain Incremental 3D Object Detection","year":2023,"lang":"en","type":"article","venue":"","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Forgetting; Artificial intelligence; Domain (mathematical analysis); Object detection; Software deployment; Scratch; Machine learning; Data mining; Pattern recognition (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":[0.0008001835,0.001181082,0.001423186,0.00114695,0.000400304,0.0008035004,0.002847012,0.0009713697,0.001322988],"category_scores_gemma":[0.002998507,0.0005888231,0.0008428551,0.001135373,0.0007138801,0.001614433,0.001529753,0.001200652,0.001564205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005978437,"about_ca_system_score_gemma":0.0007716016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004865196,"about_ca_topic_score_gemma":0.006628611,"domain_scores_codex":[0.9994185,0.00008404219,0.00002807388,0.0002026295,0.0001930026,0.00007377841],"domain_scores_gemma":[0.9992664,0.0001961625,0.00006974074,0.0002620427,0.0001503419,0.00005537536],"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":[0.000593191,0.0003994025,0.002918481,0.000258469,0.000181605,0.0002686301,0.0002922069,0.1798258,0.07860447,0.004479869,0.01618899,0.7159889],"study_design_scores_gemma":[0.00002666339,0.0001102791,0.0006758466,0.000008375099,0.00002042128,0.0002029792,0.00003023618,0.9774296,0.0151448,0.004030033,0.002293472,0.00002732205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03192555,0.0008073083,0.9600406,0.0001393666,0.00006849945,0.00009385803,0.0002595498,0.00567558,0.000989708],"genre_scores_gemma":[0.423843,0.0004454674,0.5698509,0.0004833849,0.0001369454,0.000173107,0.001959027,0.0006263119,0.002481907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004865196,"threshold_uncertainty_score":0.009673774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703549849303994,"score_gpt":0.2624631555174061,"score_spread":0.2354276570243661,"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."}}