Codebase for Berkeley Humanoid Lite. Contribute to HybridRobotics/Berkeley-Humanoid-Lite development by creating an account on GitHub.

Introducing Continuous Thought Machines

Convolutions are a type of operation that can be used to learn representations from images. They involve a learnable kernel sliding over the image and performing element-wise multiplication with the input. The specification allows for parameter sharing and…

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We explore a method for improving the performance of large language models through self-reflection and reinforcement learning. By incentivizing the model to generate better self-reflections when...

uv is an extremely fast Python package and project manager, written in Rust.

The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval - parthsarthi03/raptor

The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol. - illuin-tech/colpali

Diffusion-based language models offer a compelling alternative to autoregressive (AR) models by enabling parallel and controllable generation. Among this family of models, Masked Diffusion Models...

Vision Transformers (ViTs) have shown remarkable performance and scalability across various computer vision tasks. To apply single-scale ViTs to image segmentation, existing methods adopt a...

Self-supervised visual foundation models produce powerful embeddings that achieve remarkable performance on a wide range of downstream tasks. However, unlike vision-language models such as CLIP,...

The ability to predict future outcomes given control actions is fundamental for physical reasoning. However, such predictive models, often called world models, remains challenging to learn and are...

Self-supervised learning holds the promise of eliminating the need for manual data annotation, enabling models to scale effortlessly to massive datasets and larger architectures. By not being...

After all, you are only human.

Large language models (LLMs) have demonstrated impressive capabilities across diverse tasks, yet their ability to perform structured symbolic planning remains limited, particularly in domains...

A fast & powerful vision model that rocks.

A layer of intelligence for the physical world.
We are a research company building the future of Physical AGI.

Joint Embedding Predictive Architectures (JEPAs) learn representations able to solve numerous downstream tasks out-of-the-box. JEPAs combine two objectives: (i) a latent-space prediction term,...

Python tool for converting files and office documents to Markdown. - microsoft/markitdown