Abstract: This paper proposes a new soft-sensor approach based on the Sparse Autoencoder (Sparse AE) combined with Long Short-Term Memory (LSTM) networks. To deliver a sparse AE model, the KL ...

Researchers at DeepSeek on Monday released a new experimental model called V3.2-exp, designed to have dramatically lower inference costs when used in long-context operations. DeepSeek announced the ...

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ABSTRACT: This work contributes to the development of intelligent data-driven approaches to improve intrusion management in smart IoT environments. The proposed model combines a hybrid ...

ABSTRACT: Liver cancer is one of the most prevalent and lethal forms of cancer, making early detection crucial for effective treatment. This paper introduces a novel approach for automated liver tumor ...

According to Stanford AI Lab, researchers have successfully optimized the classic K-SVD algorithm to achieve performance on par with sparse autoencoders for interpreting transformer-based language ...

According to Chris Olah, the central issue in the ongoing Sparse Autoencoder (SAE) debate is mechanistic faithfulness, which refers to how accurately an interpretability method reflects the internal ...

Introduction: Predicting the relationship between diseases and microbes can significantly enhance disease diagnosis and treatment, while providing crucial scientific support for public health, ...