Abstract: Transformer-based methods are recently popular in vision tasks because of their capability to model global dependencies alone. However, it limits the performance of networks due to the lack ...

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

Abstract: The field of 3D medical image segmentation is witnessing a growing trend in the utilization of combined networks that integrate convolutional neural networks and transformers. Nevertheless, ...

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

This repo is used for recording, tracking, and benchmarking several recent transformer-based visual segmentation methods, as a supplement to our survey. If you find any work missing or have any ...

Traditional Large Language Models (LLMs) rely on a tokenizer (like BPE or SentencePiece) to convert text into subword tokens before feeding them to the transformer. The Byte Latent Transformer ...

We propose DPCrossU-Net, a dual-branch parallel encoder–decoder network that integrates convolutional and Vision Transformer representations. The encoder employs parallel CNN and ViT branches with a ...