This academic article introduces PosCUDA, a method to create unlearnable audio datasets. The method uses class-wise convolutions on small patches of audio, with the location of these patches based on…
Continue readingThis academic article by Anshuman Chhabra, Hadi Askari, and Prasant Mohapatra explores the concept of position bias in large language models (LLMs) and its influence on zero-shot abstractive summarization. The…
Continue readingThe research paper presents a novel uncertainty modeling framework for self-explaining neural networks. The framework aims to enhance the interpretability of deep neural networks (DNNs), which are often seen as…
Continue readingThe study explores the expressive power of Graph Neural Networks (GNNs) and their application in fields like social science, chemistry, and medicine. The authors examine the theoretical properties of GNNs,…
Continue readingThe article discusses the significance of synthetic data in the field of artificial intelligence. It emphasizes the challenges and potential biases these datasets may harbor and explores various methods of…
Continue readingThe paper discusses the limitations of current active learning approaches and proposes a new method that is model agnostic and doesn’t require an iterative process. The authors aim to use…
Continue readingThis research paper introduces a new approach called DGDNN for predicting stock movement. Traditional methods often ignore the interdependencies between stocks and the hierarchical structure of the stocks themselves. The…
Continue readingHAAQI-Net is a deep learning model designed to assess music quality for hearing aid users. It uses a Bidirectional Long Short-Term Memory (BLSTM) with attention and takes a music sample…
Continue readingThis academic paper discusses the application of machine learning and coordination in multi-robot systems, specifically in the context of robotic soccer. It provides an overview of artificial intelligence and multi-agent…
Continue readingThis study presents a vision and proprioceptive data-driven robot control model for automating anchor-bolt insertion in construction. The model is designed to be robust under variable conditions such as lighting…
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