Nyströmformer: Approximating self-attention in linear time and memory via the Nyström method

MUSE-Autoskill: Self-Evolving Agents via Skill Creation, Memory, Management, and Evaluation

Large language model (LLM) agents rely on reusable skills to solve complex tasks. However, existing skill creation approaches treat skills as isolated and static artifacts, limiting their reusability, reliability, and long-term improvement. We propose MUSE-Autoskill Agent (Memory-Utilizing Skill Evolution), a skill-...

Tokenization in Transformers v5: Simpler, Clearer, and More Modular

Universal Image Segmentation with Mask2Former and OneFormer

A failed experiment: Infini-Attention, and why we should keep trying?

Introducing Optimum: The Optimization Toolkit for Transformers at Scale

Sentence Transformers in the Hugging Face Hub