{"id":"W4401043738","doi":"10.18653/v1/2024.naacl-short.16","title":"CELI: Simple yet Effective Approach to Enhance Out-of-Domain Generalization of Cross-Encoders.","year":2024,"lang":"en","type":"article","venue":"","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Generalization; Simple (philosophy); Encoder; Computer science; Domain (mathematical analysis); Algorithm; Theoretical computer science; Mathematics","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":[0.002719388,0.001922326,0.001429224,0.001547356,0.000767912,0.001480641,0.00444086,0.001742386,0.01051834],"category_scores_gemma":[0.007093593,0.0008422835,0.001121909,0.001193763,0.0006910685,0.003786898,0.003872772,0.003623744,0.007036084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009415025,"about_ca_system_score_gemma":0.001787132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00647563,"about_ca_topic_score_gemma":0.01753482,"domain_scores_codex":[0.9988168,0.0003084686,0.00006236882,0.0003090729,0.0003257044,0.0001775874],"domain_scores_gemma":[0.9978461,0.0007209808,0.00007831062,0.0006551408,0.0005714439,0.0001280634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007927344,0.0005359231,0.00210491,0.0003399129,0.0003253908,0.0003254201,0.0002036456,0.04542437,0.0231514,0.01560277,0.08547758,0.825716],"study_design_scores_gemma":[0.0001765428,0.0002129233,0.0008358854,0.00006206765,0.0001215332,0.000262631,0.0001353477,0.9067858,0.04060715,0.02556184,0.0251802,0.00005806085],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01465566,0.001866601,0.9320471,0.0005332278,0.0005264917,0.0001851175,0.001487422,0.04216989,0.006528609],"genre_scores_gemma":[0.2569082,0.0008434539,0.7076616,0.001594372,0.0003135261,0.0005214369,0.008408561,0.003014437,0.02073443],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01051834,"threshold_uncertainty_score":0.03518736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01472647320876421,"score_gpt":0.3196598497462922,"score_spread":0.3049333765375281,"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."}}