{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001244367,0.000156933,0.0001757741,0.00003135899,0.0001576578,0.000139129,0.0002728028,0.00005504002,0.00001591641],"category_scores_gemma":[0.000009910747,0.0001272964,0.00001783665,0.0005611566,0.0000244791,0.000457982,0.00007930871,0.000155925,0.000007928137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002654509,"about_ca_system_score_gemma":0.0001025526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000738287,"about_ca_topic_score_gemma":0.0001592529,"domain_scores_codex":[0.9986785,0.00005314417,0.0001779195,0.000544714,0.0002480564,0.0002976556],"domain_scores_gemma":[0.9995142,0.00004126426,0.00002879883,0.0002049202,0.00008580878,0.0001249561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001014531,0.0003015253,0.002014211,0.0002800885,0.0004208502,0.0001806556,0.04840148,0.05166724,0.08474422,0.5161735,0.001915398,0.2928863],"study_design_scores_gemma":[0.001200626,0.000551147,0.0001684325,0.00004479479,0.00001671616,0.0000161135,0.0002301912,0.988874,0.007373747,0.000742941,0.0004406,0.0003406603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04009815,0.00006368824,0.9507298,0.001474134,0.0001222826,0.0003791385,6.090246e-7,0.0003028619,0.00682931],"genre_scores_gemma":[0.8871704,0.000009039073,0.1112882,0.001213664,0.0001252085,0.00002421317,7.130545e-7,0.00001088349,0.0001576766],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9372068,"threshold_uncertainty_score":0.5190995,"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."}}