Continuous diffusion language models

Continuous diffusion language models

Fully discrete methods dominated for a few years, but language models based on continuous diffusion are making a comeback.

An Intuitive Introduction to Flow-Based Language Generation — Floor Eijkelboom

Why autoregressive models have a structural ceiling, why discrete-diffusion LLMs are still autoregression in disguise, and what flow-based language models actually give us.

LLaDA - Large Language Diffusion Models

LLaDA is a diffusion model with an unprecedented 8B scale, rivaling LLaMA3 8B in performance.

How Stable Diffusion works

Understand in a simple way how Stable Diffusion transforms a few words into a spectacular image.

What are Diffusion Models? | IBM

Diffusion models are generative models that “diffuse” training data with random noise, then learn to reverse the diffusion process to output new images.

Beyond Standard LLMs

Linear Attention Hybrids, Text Diffusion, Code World Models, and Small Recursive Transformers

DiffusionGemma as Jev: Open-Source vLLM Patch (2026) | explainx.ai Blog

A vLLM contributor built an open-source Jev clone using DiffusionGemma — roughly matching TypeSafe's proprietary model on accuracy.

Models overview

Claude is a family of state-of-the-art large language models developed by Anthropic. This guide introduces the available models and compares their performance.

Scaling Laws Across Model Architectures: A Comparative Analysis of...

The scaling of large language models (LLMs) is a critical research area for the efficiency and effectiveness of model training and deployment. Our work investigates the transferability and...

The Case Against LLMs as Rerankers

Authors: Apoorva Joshi, Zhenmei Shi, Akshay Goindani, Hong LiuResearch Leads: Zhenmei Shi, Akshay Goindani, Hong Liu Large language models are increasingly being used for a broad range of tasks, in…

Inference-Time Scaling for Generative Pre-Training | Jiaming Song

A short note on the false dichotomy between autoregression and diffusion, why flow maps help, and what this might mean for language models.

Recursive Language Models: the paradigm of 2026

How we plan to manage extremely long contexts

Large language models are cultural technologies. What might that mean?

Four different perspectives