Recent efforts in naturallanguageprocessing (NLP) commonsense reasoning research have led to the development of numerous new datasets and benchmarks. However, these resources have predominantly been limited to Engli...
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Stance detection, a naturallanguageprocessing technique, captures user attitudes on controversial social media topics. However, the semantic ambiguity of social texts makes accurate stance determination challenging....
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Multi-phase contrast-enhanced computed tomography (CECT) has been shown to effectively refine the segmentation accuracy for both tumors and organs. Nevertheless, enhancing the segmentation accuracy of the pancreas and...
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Visual language Models (VLMs) have rapidly progressed with the recent success of large language models. However, there have been few attempts to incorporate efficient linear Recurrent Neural Networks (RNNs) architectu...
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Incorporating cyber artifacts into Cyber-Socio-Technical Systems (CSTSs) poses new challenges to human safety due to their increasingly unpredictable behavior. Resilience is the ability to adapt, recover, and bounce b...
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The increasing use of Romanized typing for Indo-Aryan languages on social media poses challenges due to its lack of standardization and loss of linguistic richness. To address this, we propose a sentence-level back-tr...
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Query-focused summarization (QFS) is a fundamental task in naturallanguageprocessing with broad applications, including search engines and report generation. However, traditional approaches assume the availabil...
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The virtual simulation testing and verification of autonomous driving systems require large-scale test scenarios. Existing methods for scenario construction are often limited by human experience in user interaction an...
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Sentiment analysis, a pivotal aspect of naturallanguageprocessing (NLP), has seen notable advancements with the advent of deep learning models. Despite these advancements, challenges persist in accurately capturing ...
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Most available data is unstructured, making it challenging to access valuable information. Automatically building knowledge Graphs (KGs) is crucial for structuring data and making it accessible, allowing users to sear...
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