eLife

Reconstructing voice identity from noninvasive auditory cortex recordings

A low-dimensional voice latent space derived from deep learning captures speaker-identity representations in the temporal voice areas and supports reconstruction of voices preserving identity ...

How neuron groups team up to embed memories in context

Humans have the remarkable ability to remember the same person or object in completely different situations. We can easily ...

Meta’s Vision-Language Shift VL-JEPA Beats Bulky LLMs

VL-JEPA predicts meaning in embeddings, not words, combining visual inputs with eight Llama 3.2 layers to give faster answers ...

Word embeddings in NLP

We will discuss word embeddings this week. Word embeddings represent a fundamental shift in natural language processing (NLP) ...
IEEE

Data-Driven Motion Planning: A Survey on Deep Neural Networks, Reinforcement Learning, and Large Language Model Approaches

Abstract: Motion planning is a fundamental challenge in robotics, involving the creation of trajectories from start to goal states while meeting constraints like collision avoidance and joint limits.
IEEE

Model Steganography During Model Compression

Abstract: Recently, many compressed neural network models have been implemented on embedded platforms. However, there is still a lack of steganographic methods that utilizes these compressed models ...
san

Preschool network Head Start sues feds over ‘word ban’ of DEI terms

Head Start, an early-childhood network that pairs classroom learning with health and family support systems for infants through preschoolers at 1,600 local agencies, now faces new language curbs on ...
Frontiers

Relationship between intrahemispheric and interhemispheric connectivity of the language network and language improvement in subacute post-stroke aphasia

Speech production and comprehension are coordinated by a large-scale language network. The dynamic balance of intrahemispheric and interhemispheric connectivity within this network is essential for ...