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aistairc avatar

aistairc/text-diff-2step-loss

0
View on GitHub↗
5 stars·0 forks·Python·Apache-2.0·9 views

Text Diff 2step Loss

The implementation of "Addressing the Training-Inference Discrepancy in Discrete Diffusion for Text Generation"

Features

  • Training and Alignment - Addressing training-inference discrepancy in discrete diffusion.

Star history

Star history chart for aistairc/text-diff-2step-lossStar history chart for aistairc/text-diff-2step-loss

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Text Diff 2step Loss

These projects share indexed features with Text Diff 2step Loss. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • apple/ml-diffucoderapple avatar

    apple/ml-diffucoder

    825View on GitHub↗

    This software project accompanies the research paper, DiffuCoder: Understanding and Improving Masked Diffusion Models for Code Generation.

    Python
    View on GitHub↗825
  • autonomousvision/mdpoautonomousvision avatar

    autonomousvision/mdpo

    44View on GitHub↗

    [Paper](https://arxiv.org/pdf/2508.13148) [Project](https://cli212.github.io/MDPO/)

    Python
    View on GitHub↗44
  • bhmingyang/tadBHmingyang avatar

    BHmingyang/TAD

    2View on GitHub↗

    ```bash conda create -n tad python=3.10 -y conda activate tad

    Python
    View on GitHub↗2
  • amap-ml/ar-mapAMAP-ML avatar

    AMAP-ML/AR-MAP

    24View on GitHub↗

    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

    Python
    View on GitHub↗24
Compare all 25 related projects→

Frequently asked questions

What does aistairc/text-diff-2step-loss do?

The implementation of "Addressing the Training-Inference Discrepancy in Discrete Diffusion for Text Generation"

What are the main features of aistairc/text-diff-2step-loss?

The main features of aistairc/text-diff-2step-loss are: Training and Alignment.

Which projects share features with aistairc/text-diff-2step-loss?

Projects with overlapping indexed features include: 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. chenyuwang-monica/drakes — The repository contains the code for the DRAKES method presented in the paper: Fine-Tuning Discrete Diffusion Models… amap-ml/ar-map — Are Autoregressive Large Language Models Implicit Teachers for Diffusion Large Language Models? A comprehensive…