Sleep stage classification from single-channel electroencephalography (EEG) is essential for wearable and home-based sleep monitoring. However, many deep learning models achieve high accuracy at the cost of large model sizes, which limits their deployment on resource-constrained devices. In this work, we present NanoSl...
Recent improvements in voice-cloning speech generation systems raise concerns about misuse by malicious actors to impersonate others and spread misinformation. Detecting such tampering is difficult, since deepfakes in the wild may be created by different generative models in a wide range of languages. Furthermore, the...
Yuan Tseng, Aishwarya Fursule, Andrew Zijun Ma et al.· 0 citations
Accurate sleep staging is essential for characterizing sleep architecture, yet conventional polysomnography limits scalable and long-term sleep monitoring. Wearable sensors offer a practical alternative, but their performance depends on the physiological modalities used and how the signals are represented. This study i...
Unaza Tallal, Rupesh Agrawal, S. Kshirsagar· Italian National Conference...· 0 citations
Examining the influence of the RAG framework, comprising ideological discourses, in LLM-generated answers shows that the RAG framework is prone to transferring ideological discourses into LLM responses, with sampling temperature having a measurable impact on the strength of this transfer.
Elmira Salari, H. Amamou, J. V. D. de Souza et al.· arXiv.org· 0 citations
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