Meta’s Brain2Qwerty v2 offers a breakthrough non-invasive brain-to-text AI model with 61% word accuracy, challenging ...

Abstract: U-shaped encoder-decoder models have excelled in automatic medical image segmentation due to their hierarchical feature learning capabilities, robustness, and upgradability. Purely CNN-based ...

Abstract: We propose a novel solution for predicting future trajectories of pedestrians. Our method uses a multimodal encoder-decoder transformer architecture, which takes as input both pedestrian ...

Open-source OCR from Baidu eliminates the GPU memory wall that limits long-document parsing. Unlimited OCR uses a constant KV ...

These local LLMs are changing the game in lots of fun ways.

Reimplement the original encoder-decoder Transformer end to end in PyTorch, from token vocabularies and sinusoidal positional encodings through multi-head attention, label smoothing, Noam scheduling, ...

Reimplement the original encoder-decoder Transformer end to end in PyTorch, from token vocabularies and sinusoidal positional encodings through multi-head attention, label smoothing, Noam scheduling, ...

To address this challenge, this paper proposes the Graph Attention Enhanced Scale-Aware Inverted Transformer (GAESA-iFormer), a novel surrogate modeling framework integrating a Graph Attention Network ...