A type of artificial intelligence that focuses on designing systems that can learn from and make decisions based on data.
The research introduces a low-cost mobile manipulation system, Mobile ALOHA, that is bimanual and supports whole-body teleoperation. This system enhances the ALOHA system with a mobile base and a whole-body…
Continue readingThe research paper presents L3Cube-IndicNews, a multilingual text classification corpus specifically focusing on news headlines and articles in Indian regional languages. This includes Hindi, Bengali, Marathi, Telugu, Tamil, Gujarati, Kannada,…
Continue readingThis academic paper presents a new framework for predicting temperature fields in real-time during metal additive manufacturing (AM) processes. The authors argue that accurate temperature prediction is essential to prevent…
Continue readingThis paper presents a new approach to predicting temperature fields in metal additive manufacturing (AM) using a physics-informed neural network framework. Traditional physics-based models are often time-consuming and unsuitable for…
Continue readingThe article introduces an innovative architecture to estimate causal effects from data spread across different silos. The architecture’s design allows for the seamless transmission of model parameters enriched with causal…
Continue readingThis paper explores the role of artificial intelligence (AI) in the metaverse, particularly focusing on collaborative deep learning (CDL). It identifies potential security risks, such as malicious participants and GAN-attacks,…
Continue readingThis paper proposes a reputation-based federated learning framework to mitigate potential security threats in EEG signal classification. The framework is useful in the growing field of brain-computer interface technology, where…
Continue readingThis research paper examines the vulnerability of Integrated Circuit (IC) supply chains to Hardware Trojans (HTs). The authors introduce a new approach to HT obfuscation that allows HTs to bypass…
Continue readingThis 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 readingThe research presents a novel approach to enhance the understanding of tabular data extracted from PDFs for efficient summarization by language models. The approach involves storing PDFs in the retrieval…
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