Abstract: In the context of Electroencephalography (EEG) research, how is Working Memory (WM) leveraged in Human-Computer Interaction (HCI)? To address this question, this paper explores how WM is ...

A new study shows that the human brain stores what we remember and the context in which it happens using different neurons.

Early-2026 explainer reframes transformer attention: tokenized text becomes Q/K/V self-attention maps, not linear prediction.

Abstract: Dedicated neural-network inference-processors improve latency and power of the computing devices. They use custom memory hierarchies that take into account the flow of operators present in ...

Abstract: The physics mechanism behind the polarity effect at the basis of the Single-chalcogenide Xpoint Memory (SXM) is investigated through dedicated experiments, DFT-based atomistic models and ...

Abstract: This paper proposes a framework for deep Long Short-Term Memory (D-LSTM) network embedded model predictive control (MPC) for car-following control of connected automated vehicles (CAVs) in ...

Abstract: In this work, based on finite element method, a physics-based equivalent circuit model for polycrystalline hafnia-based 3D ferroelectric capacitor is proposed and developed, which can ...

Abstract: In order to represent the influences of different semantics on targets and improve the prediction with interpretability ability for multi-dimensional time series, we integrate Axiomatic ...

Abstract: Digital in-memory compute (IMC) architectures allow for a balance of the high accuracy and precision necessary for many machine learning applications, with high data reuse and parallelism to ...

Abstract: This paper introduces a novel Large Language Model (LLM)-based system designed to enhance learning effect through Socratic inquiry, thereby fostering deep understanding and longterm ...

It’s all hands on deck at Meta, as the company develops new AI models under its superintelligence lab led by Scale AI co-founder, Alexandr Wang. The company is now working on an image and video model ...

Abstract: Neural network models have been widely used in various fields as the main way to solve problems in the current artificial intelligence (AI) field. Efficient execution of neural network ...