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Titlebook: Natural Language Processing and Information Systems; 28th International C Elisabeth Métais,Farid Meziane,Stephan Reiff-Marga Conference pro

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楼主: 毛发
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Large Language Models in the Workplace: A Case Study on Prompt Engineering for Job Type Classificatiropriate for a graduate or entry-level position. We explore multiple approaches to text classification, including supervised approaches such as traditional models like Support Vector Machines (SVMs) and state-of-the-art deep learning methods such as .. We compare them with Large Language Models (LLM
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How Challenging is Multimodal Irony Detection?odal irony. Over the last years, a series of approaches have emerged trying to leverage all these formats to address the problem of multimodal irony detection. The question that the present work tries to answer is whether multimodal irony systems are being properly evaluated. More specifically, this
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Explaining a Deep Learning Model for Aspect-Based Sentiment Classification Using Post-hoc Local Class to explain the outcome of a black box state-of-the-art deep learning model used for ABSC, LCR-Rot-hop++. We compare two sampling methods that feed an interpretability algorithm which is based on local linear approximations (LIME). One of the sampling methods, SS, swaps out different words from the
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Arabic Privacy Policy Corpus and Classificationmers find it difficult to read and become unaware of the content. To simplify it for consumers, an automatic technique verifies whether websites and applications comply with the established privacy and data protection laws in companies worldwide. The implementation of the Personal Data Protection La
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Explainable Integration of Knowledge Graphs Using Large Language Modelsclarative link discovery frameworks use complex link specifications to express the conditions under which a link between two resources can be deemed to exist. However, understanding such complex link specifications is a challenging task for non-expert users of link discovery frameworks. In this pape
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