Discourse relation classification is a fundamental task for discourse analysis, which is essential for understanding the structure and connection of texts. Implicit discourse relation classification aims to determine the relationship between adjacent sentences and is the most challenging in discourse relation classification because it lacks explicit discourse connectives as linguistic cues and sufficient annotated training data.Discourse relation classification is a fundamental task for discourse analysis, which is essential for understanding the structure and connection of texts. Implicit discourse relation classification aims to determine the relationship between adjacent sentences and is the most challenging in discourse relation classification because it lacks explicit discourse connectives as linguistic cues and sufficient annotated training data.[#item_full_content]

New research reveals that synchronized foot vibrations and posture significantly enhance virtual walking experiences for stationary observers, improving self-motion, walking sensation, and embodiment. Standing posture was most effective, but sitting and lying positions also benefited from synchronized vibrations. These findings have practical applications in virtual reality (VR) for training, rehabilitation, and entertainment, offering improved immersion and realism even for users with physical limitations.New research reveals that synchronized foot vibrations and posture significantly enhance virtual walking experiences for stationary observers, improving self-motion, walking sensation, and embodiment. Standing posture was most effective, but sitting and lying positions also benefited from synchronized vibrations. These findings have practical applications in virtual reality (VR) for training, rehabilitation, and entertainment, offering improved immersion and realism even for users with physical limitations.[#item_full_content]

Automatic bug assignment has been well studied in the past decade. As textual bug reports usually describe the buggy phenomena and potential causes, engineers highly depend on these reports to fix bugs. Researchers heavily depend on the textual content in the bug reports to locate the buggy files. However, noises in texts bring adverse impacts to automatic bug assignments unexpectedly, mainly due to insufficiency of classical Natural Language Processing (NLP) techniques.Automatic bug assignment has been well studied in the past decade. As textual bug reports usually describe the buggy phenomena and potential causes, engineers highly depend on these reports to fix bugs. Researchers heavily depend on the textual content in the bug reports to locate the buggy files. However, noises in texts bring adverse impacts to automatic bug assignments unexpectedly, mainly due to insufficiency of classical Natural Language Processing (NLP) techniques.[#item_full_content]

Last week, quantum computers were added to Australia’s Defense and Strategic Goods List of controlled items facing export restrictions. That’s because quantum technologies—which may soon provide huge advances in computing, communication and sensing—are rapidly growing in strategic importance.Last week, quantum computers were added to Australia’s Defense and Strategic Goods List of controlled items facing export restrictions. That’s because quantum technologies—which may soon provide huge advances in computing, communication and sensing—are rapidly growing in strategic importance.[#item_full_content]

Researchers from EPFL have developed a next-generation miniaturized brain-machine interface capable of direct brain-to-text communication on tiny silicon chips.Researchers from EPFL have developed a next-generation miniaturized brain-machine interface capable of direct brain-to-text communication on tiny silicon chips.[#item_full_content]

The most recent email you sent was likely encrypted using a tried-and-true method that relies on the idea that even the fastest computer would be unable to efficiently break a gigantic number into factors.The most recent email you sent was likely encrypted using a tried-and-true method that relies on the idea that even the fastest computer would be unable to efficiently break a gigantic number into factors.[#item_full_content]

Training deep learning models on large datasets is essential for their success; however, these datasets often contain label noise, which can significantly decrease the classification performance on test datasets.Training deep learning models on large datasets is essential for their success; however, these datasets often contain label noise, which can significantly decrease the classification performance on test datasets.[#item_full_content]

A research team has developed a computer vision technique that can perform dichotomous image segmentation, high-resolution salient object detection, and concealed object detection in the same framework. Their novel bilateral reference framework (BiRefNet) is able to capture tiny-pixel features and holds potential for a wide range of practical computer vision applications.A research team has developed a computer vision technique that can perform dichotomous image segmentation, high-resolution salient object detection, and concealed object detection in the same framework. Their novel bilateral reference framework (BiRefNet) is able to capture tiny-pixel features and holds potential for a wide range of practical computer vision applications.[#item_full_content]

A team of AI researchers and computer scientists at the University of Alberta has found that current artificial networks used with deep-learning systems lose their ability to learn during extended training on new data. In their study, reported in the journal Nature, the group found a way to overcome these problems with plasticity in both supervised and reinforcement learning AI systems, allowing them to continue to learn.A team of AI researchers and computer scientists at the University of Alberta has found that current artificial networks used with deep-learning systems lose their ability to learn during extended training on new data. In their study, reported in the journal Nature, the group found a way to overcome these problems with plasticity in both supervised and reinforcement learning AI systems, allowing them to continue to learn.[#item_full_content]

A team of Chinese scientists has established a novel brain-inspired network model based on internal complexity to address challenges faced by traditional models, such as high consumption of computing resources, according to the Institute of Automation under the Chinese Academy of Sciences.A team of Chinese scientists has established a novel brain-inspired network model based on internal complexity to address challenges faced by traditional models, such as high consumption of computing resources, according to the Institute of Automation under the Chinese Academy of Sciences.[#item_full_content]