Recent advancements in training large multimodal models have been driven by efforts to eliminate modeling constraints and unify architectures across domains. Despite these strides, many existing ...

The Transmission Company of Nigeria (TCN) has taken a significant step in enhancing electricity supply with the commissioning of a 1×60/75 MVA 132/33KV power transformer at the 330/132/33kV Lekki ...

Central to Sapient’s success is its hybrid architecture that blends Transformer components with recurrent neural network structures.

Transformers One has now landed on digital platforms in the UK following its earlier release in the US in October. The animated prequel is the untold origin story of Optimus Prime and Megatron who ...

High voltage electricity in power lines is exclusively appropriate for long-distance power transmission. For practical applications, electricity must travel through a transformer that adjusts its ...

This paper bridges this gap through the design and evaluation of the Elastic Time-Series Transformer (ElasTST). The ElasTST model incorporates a non-autoregressive design with placeholders and ...

A better name would be Autoregressive Transformers or something. They don’t care if the tokens happen to represent little text chunks. It could just as well be little image patches, audio chunks ...

Autoregressive models are used to generate sequences of discrete tokens ... They processed the data with Music2Latent to create continuous latent embeddings with a 12 Hz sampling rate. Based on a ...

[NeurIPS 2024 Oral][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An ...