Titlebook: Natural Language Processing and Information Systems; 29th International C Amon Rapp,Luigi Di Caro,Vijayan Sugumaran Conference proceedings

无思维能力

,Large-Scale Language Models for Sarcasm Detection with Data Augmentation, of popular large-scale language models, such as BERT, XLNet and their variants. Experimental results demonstrated that human labelled data can significantly boost the detection accuracy of these language models, while noising data augmentation technique yields negative results.

CREST

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,E-ReaRev: Adaptive Reasoning for Question Answering over Incomplete Knowledge Graphs by Edge and Metional resources. Furthermore, a new meaning-extension module is introduced to incorporate semantic information of entities into node representations with lower memory consumption. Experimental results on two datasets demonstrate the effectiveness of proposed method compared with other baselines und

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,ECR: An Expertise-Enriched Conclude-Then-Refine Summarization Framework for Professional Articles, professionalism. Experimental results indicate that our approach offers superior summaries to the summaries generated by the common method across diverse domains. ECR shows an over 80% win rate in structural consistency evaluated by the LLM, alongside a 2x increase in terminology integration. The f

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,Issue Links Retrieval for New Issues in Issue Tracking Systems, with respect to a given link type . to build issue links (., ., .). This paper presents novel methods using pre-trained language models (e.g., GPT-2) to embed issue links for computing probability scores to retrieve issue links. Our methods are evaluated on four datasets, demonstrating high effecti

Euphonious

,Evaluation of Gender Bias in Amharic Word Embedding Model,he arts and athleticism demonstrate a robust female-leaning bias, while physically demanding and educated professional roles tend to exhibit male-leaning biases. The study contributes insights into the gender dynamics encoded within the Amharic language informing strategies to reduce bias and foster

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,Question Generation Capabilities of “Small" Large Language Models,ing on the used transformer architecture, which indicates a correlation between transformer architecture and question structure. Furthermore, different search strategies for the same model architecture do not greatly impact structure or quality.

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