Recent advances in Large Language Models (LLMs) have enabled the semantic description of textures in natural language, aiming to capture them in richer detail. However, most methods are confined to either depending on...
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Recently, evolutionary multitasking has been employed to generate a 'set of Pareto sets' (SOS) for machine learning models, addressing diverse task settings across heterogeneous environments. This involves cre...
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Lane change intention prediction is critical in improving road safety. In general, this task is achieved via two distinct approaches: The data-based approach and the rule-based approach. Generally, the former outperfo...
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Recent studies on generalizable object detection have attracted increasing attention with additional weak supervision from large-scale datasets with image-level labels. However, weakly-supervised detection learning of...
This paper aims to identify trends in perceptions on the topic of globalization by performing sentiment analysis on text data collected from social media posts. A novel methodology of extracting culture-informed senti...
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This paper explores the integration of large language models (LLMs) into the curriculum design process for short-term adult training programs, highlighting the role of prompt engineering as a transformative tool. As a...
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Music visualization is presented in different formats. The mainstream music visualization remains focused on providing animated images for visual pleasure or for enhancing the perception of sheet music with colors. St...
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Existing autonomous vehicles have not utilized the cloud computing for execution of their deep learning-based driving tasks due to the long vehicle-to-cloud communication latency. Meanwhile, the vehicles are in genera...
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Human activities are inherently task-oriented, and integrating explicit task learning into action segmentation models is hypothesized to enhance performance. However, empirical evaluations using the Ego4D Goal Step da...
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Knowledge-based Visual Qustion-answering (K-VQA) often requires the use of background knowledge beyond the image. However, we discover that a single knowledge generation strategy is often insufficient for all K-VQA qu...
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