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näkemys - Weakly Supervised Learning
RulePrompt: Weakly Supervised Text Classification with Prompting PLMs and Self-Iterative Logical Rules
The authors propose RulePrompt, a novel approach that leverages logical rules to enhance the understanding of categories in weakly supervised text classification tasks using prompting PLMs.
SCARCE: A Novel Approach for Complementary-Label Learning
提案されたSCARCEアプローチは、均一な分布仮定や通常のラベルトレーニングセットに依存せず、一貫性のある補完ラベル学習を実現します。
Learning from Reduced Labels for Long-Tailed Data Analysis
Introducing Reduced Labels for Long-Tailed Data to preserve supervised information and decrease labeling costs.
Complementary Label Learning without Assumptions: SCARCE Approach
SCARCE proposes a consistent approach for complementary-label learning without relying on distribution assumptions, showing superior performance.
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