Titlebook: Chinese Computational Linguistics; 22nd China National Maosong Sun,Bing Qin,Yubo Chen Conference proceedings 2023 The Editor(s) (if applic

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Enhancing Ontology Knowledge for?Domain-Specific Joint Entity and?Relation Extractionetween general-domain text used for pre-training and domain-specific text, these methods encounter semantic redundancy and domain semantics insufficiency when it comes to domain-specific tasks. To mitigate this issue, we propose a low-cost and effective knowledge-enhanced method to facilitate domain

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Native Bridging in React Native,Graph Network (GN) and Question Decomposition (QD) are two common approaches at present. The former uses the “black-box” reasoning process to capture the potential relationship between entities and sentences, thus achieving good performance. At the same time, the latter provides a clear reasoning lo

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The Ecosystem: Extending React Native,ditions. CQA is crucial for domains that require the provision of personalized advice or making context-dependent analyses, such as legal consulting and medical diagnosis. However, existing CQA models struggle with generating multiple conditional answers due to two main challenges: (1) the lack of s

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React Native for iOS Development efforts, causal inference is regarded as a promising direction to mitigate language bias by weakening the direct causal effect of questions on answers. In this paper, we follow the same direction and attack the issue of language priors by incorporating counterfactual data. Moreover, we propose a tw

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Flux: Solving Problems Differently,, supporting sentence prediction, and answer span extraction. In this work, we present the first application of label smoothing to the MHQA task, aiming to enhance generalization capabilities in MHQA systems while mitigating overfitting of answer spans and reasoning paths in the training set. We int

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Starter React Project and Friends,g data is one of the main problems in this field. In this work, we design a .iscrete style space for unsupervised .eadline .tyle .ransfer, short for .. This model decomposes the style-dependent text generation into content-feature extraction and style modelling. Then, generation decoder receives inp

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E. J. Lous,M. Huber,R. A. Isaacson,G. Feherical complexity controlled sentence generation, which requires precise control over the lexical complexity in the keywords to examples generation and better fluency and semantic consistency. The challenge of this task is to generate fluent sentences only using words of given complexity levels. We pr

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