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ChenyuWang-Monica avatar

ChenyuWang-Monica/DRAKES

0
View on GitHub↗
72 stars·13 forks·Python·9 views

DRAKES

The repository contains the code for the DRAKES method presented in the paper: Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein design (ICLR 2025). DRAKES is a fine-tuning method for reward optimization or alignment in discrete diffusion models,…

Features

  • Applications - Reward-optimized fine-tuning for protein and DNA design.
  • Applied Diffusion Models - Fine-tunes models via reward optimization for biological sequence design.
  • Training and Alignment - Reward optimization for discrete diffusion in biological design.

Star history

Star history chart for chenyuwang-monica/drakesStar history chart for chenyuwang-monica/drakes

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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Frequently asked questions

What does chenyuwang-monica/drakes do?

The repository contains the code for the DRAKES method presented in the paper: Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein design (ICLR 2025). DRAKES is a fine-tuning method for reward optimization or alignment in discrete diffusion models,…

What are the main features of chenyuwang-monica/drakes?

The main features of chenyuwang-monica/drakes are: Applications, Applied Diffusion Models, Training and Alignment.

Which projects share features with chenyuwang-monica/drakes?

Projects with overlapping indexed features include: bytedance/dplm — This repository contains the official implementation of training and inference as well as the pre-trained weights for… apple/ml-diffucoder — This software project accompanies the research paper, DiffuCoder: Understanding and Improving Masked Diffusion Models… amayama/xdlm. apple/ml-planner — PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model. autonomousvision/mdpo — [[Paper]](https://arxiv.org/pdf/2508.13148) [[Project]](https://cli212.github.io/MDPO/). amap-ml/ar-map — Are Autoregressive Large Language Models Implicit Teachers for Diffusion Large Language Models? A comprehensive…

Projects sharing features with DRAKES

These projects share indexed features with DRAKES. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • bytedance/dplmbytedance avatar

    bytedance/dplm

    339View on GitHub↗

    This repository contains the official implementation of training and inference as well as the pre-trained weights for the Family of Diffusion Protein Language Models (DPLM), including: - DPLM from ICML'24 paper "Diffusion Language Models Are Versatile Protein Learners", which introduces…

    Python
    View on GitHub↗339
  • 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
  • amayama/xdlmA

    Amayama/XDLM

    0View on GitHub↗
    View on GitHub↗0
  • 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
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