{"id":"W3035044482","doi":"10.18653/v1/2020.acl-main.128","title":"Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network","year":2020,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":189,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"National Natural Science Foundation of China","keywords":"Computer science; Artificial intelligence; Shot (pellet); Conditional random field; Dependency (UML); Projection (relational algebra); Similarity (geometry); Task (project management); Semantics (computer science); Transfer of learning; Pattern recognition (psychology); Word (group theory); Representation (politics); Multi-label classification; Natural language processing; Machine learning; Algorithm; Image (mathematics); 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":[0.001155522,0.00132294,0.001179746,0.0008745434,0.0008587329,0.0008119522,0.002384127,0.001668668,0.002298657],"category_scores_gemma":[0.002777649,0.0005568858,0.0009551298,0.001258467,0.0008046236,0.004321892,0.00202835,0.002211639,0.001349005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008002978,"about_ca_system_score_gemma":0.001314201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004946218,"about_ca_topic_score_gemma":0.009743071,"domain_scores_codex":[0.9991673,0.0002233158,0.00002627016,0.0003808002,0.0001094005,0.00009295781],"domain_scores_gemma":[0.9986479,0.0006258422,0.00009041608,0.0002690938,0.0002475796,0.0001192472],"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":[0.0008064985,0.000843338,0.007018524,0.0004300253,0.0001925661,0.0007283196,0.0009088663,0.1746259,0.02137312,0.01690707,0.01758694,0.7585789],"study_design_scores_gemma":[0.00001372615,0.00008004688,0.0005452602,0.00001572034,0.00003152841,0.0001106931,0.00005897043,0.9798782,0.003059075,0.01441669,0.001767359,0.00002271774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07846897,0.00101641,0.9112971,0.0005097869,0.0002306631,0.0001767395,0.0005924755,0.004122447,0.003585441],"genre_scores_gemma":[0.7605639,0.000610311,0.2203494,0.0006094339,0.0002120821,0.0003975348,0.00349478,0.0003320023,0.01343048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004946218,"threshold_uncertainty_score":0.009834886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03743755894945409,"score_gpt":0.2290466441536378,"score_spread":0.1916090852041837,"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."}}