Are Autoregressive Large Language Models Implicit Teachers for Diffusion Large Language Models? A comprehensive framework for transferring alignment knowledge from AR-LLMs to Diffusion Models
This software project accompanies the research paper, DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation.
[Paper](https://arxiv.org/pdf/2508.13148) [Project](https://cli212.github.io/MDPO/)
The implementation of "Addressing the Training-Inference Discrepancy in Discrete Diffusion for Text Generation"
This is the official implementation of the paper d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation (ICML'26), where we introduce a novel recipe for building an ultra-fast diffusion language model named d3LLM (pseuDo-Distilled Diffusion LLM) 🚀.
Die Hauptfunktionen von hao-ai-lab/d3llm sind: Training and Alignment.
Open-Source-Alternativen zu hao-ai-lab/d3llm sind unter anderem: amap-ml/ar-map — Are Autoregressive Large Language Models Implicit Teachers for Diffusion Large Language Models? A comprehensive… apple/ml-diffucoder — This software project accompanies the research paper, DiffuCoder: Understanding and Improving Masked Diffusion Models… autonomousvision/mdpo — [[Paper]](https://arxiv.org/pdf/2508.13148) [[Project]](https://cli212.github.io/MDPO/). bhmingyang/tad — ```bash conda create -n tad python=3.10 -y conda activate tad. bowen-sun-0728/blockwise-sft — Blockwise SFT for Diffusion Language Models: Reconciling Bidirectional Attention and Autoregressive Decoding. aistairc/text-diff-2step-loss — The implementation of "Addressing the Training-Inference Discrepancy in Discrete Diffusion for Text Generation".