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Toward fair graph neural networks via real counterfactual samples
Graph neural networks (GNNs) have become pivotal in various critical decision-making scenarios due to their exceptional performance. However,...
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Psychosocial factors that favor citizen participation in the generation of scientific knowledge
BackgroundCitizen participation in the generation of scientific knowledge is one of the major challenges facing science and technology systems. This...
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Aspect-based drug review classification through a hybrid model with ant colony optimization using deep learning
The task of aspect-level sentiment analysis is intricately designed to determine the sentiment polarity directed towards a specific target within a...
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Applicability of large language models and generative models for legal case judgement summarization
Automatic summarization of legal case judgements, which are known to be long and complex, has traditionally been tried via extractive summarization...
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Unveiling intrusions: explainable SVM approaches for addressing encrypted Wi-Fi traffic in UAV networks
Unmanned aerial vehicles (UAVs), also known as drones, have become instrumental in various domains, including agriculture, geographic information...
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Cooperative coati optimization algorithm with transfer functions for feature selection and knapsack problems
Coatis optimization algorithm (COA) has recently emerged as an innovative meta-heuristic algorithm (MA) for global optimization, garnering...
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Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
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How to measure interdisciplinary research? A systemic design for the model of measurement
Interdisciplinarity is a polysemous concept with multiple, reasoned and intuitive, interpretations across scholars and policy-makers. Historically,...
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Are reviewer scores consistent with citations?
Academic evaluation is a critical component of research, with the interaction between quantitative and qualitative assessments becoming a prominent...
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SIM-GCN: similarity graph convolutional networks for charges prediction
In recent years, the analysis of legal judgments and the prediction of outcomes based on case factual descriptions have become hot research topics in...
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From PARIS to LE-PARIS: toward patent response automation with recommender systems and collaborative large language models
In patent prosecution, timely and effective responses to Office Actions (OAs) are crucial for securing patents. However, past automation and...
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From informal to formal: scientific knowledge role transition prediction
Comprehending the patterns of knowledge evolution benefits funding agencies, policymakers, and researchers in develo** creative ideas. We introduce...
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HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer...
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The cost of open access: comparing public projects’ budgets and article processing charges expenditure
Open Access (OA) publication often entails payment of Article processing charges (APCs), particularly in the so-called Hybrid and Gold journals. The...
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Linguistic perspectives in deciphering citation function classification
Understanding citations within their context is a complex task in information science, critical for bibliometric analysis. The study of citation...
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De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network
Counterfactual inference for continuous rather than binary treatment variables is more common in real-world causal inference tasks. While there are...
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Exploring the potential of Easy Language for enhancing website sustainability
Sustainable design principles have become increasingly important in website development, mainly focusing on reducing carbon emissions and energy...
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Gradient-based explanation for non-linear non-parametric dimensionality reduction
Dimensionality reduction (DR) is a popular technique that shows great results to analyze high-dimensional data. Generally, DR is used to produce...
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Enhancing racism classification: an automatic multilingual data annotation system using self-training and CNN
Accurate racism classification is crucial on social media, where racist and discriminatory content can harm individuals and society. Automated racism...