{"id":"W3207180064","doi":"10.48550/arxiv.2101.10423","title":"Online Continual Learning in Image Classification: An Empirical Survey","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Forgetting; Computer science; Machine learning; Artificial intelligence; Classifier (UML); Class (philosophy); Variety (cybernetics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009067278,0.0002720701,0.0003751403,0.000318024,0.0001441278,0.0003698984,0.001322713,0.0002963288,0.00007861658],"category_scores_gemma":[0.0003050191,0.0003471475,0.0001250693,0.001029108,0.0001079852,0.0007167283,0.001111204,0.001398782,0.00004784855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001958046,"about_ca_system_score_gemma":0.0004453829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003023031,"about_ca_topic_score_gemma":0.001200422,"domain_scores_codex":[0.99656,0.001350184,0.0003104699,0.00128367,0.000142402,0.0003532159],"domain_scores_gemma":[0.9980258,0.0002813035,0.0002807375,0.0008767234,0.0003242943,0.0002110773],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001182759,0.001575635,0.5657156,0.00009458663,0.0001204019,0.002358732,0.005839985,0.3875899,0.0004284613,0.02484679,0.0003684036,0.01094324],"study_design_scores_gemma":[0.0003871505,0.00003307699,0.3843866,0.00003568803,0.000007299137,0.000003294382,0.0008386225,0.613113,0.00000705326,0.0003269081,0.0005715645,0.0002896685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5546237,0.00002394684,0.4435716,0.0001556754,0.0002345801,0.0001047597,0.00000617696,0.0001966208,0.001082971],"genre_scores_gemma":[0.9899626,0.00006849453,0.007597597,0.0001708156,0.00005574374,6.510717e-7,0.0003341505,0.00001933284,0.001790664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.435974,"threshold_uncertainty_score":0.9998981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1961559989774746,"score_gpt":0.2663611067145922,"score_spread":0.07020510773711755,"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."}}