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Found 4 papers, 1 papers with code
ProSwitch: Knowledge-Guided Instruction Tuning to Generate Professional and Non-Professional Styled Text
Large Language Models (LLMs) have demonstrated efficacy in various linguistic applications, including text summarization and controlled text generation.
KeNet:Knowledge-enhanced Doc-Label Attention Network for Multi-label text classification
It is imperative to additionally acknowledge that the significance of knowledge is substantiated in the realm of MLTC.
Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation
In this research, we argue that the evidences of an answer is critical to enhancing the interpretability of QA models.
Constrained Linear Data-feature Mapping for Image Classification
In this paper, we propose a constrained linear data-feature mapping model as an interpretable mathematical model for image classification using convolutional neural network (CNN) such as the ResNet.
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