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Johnny221B avatar

Johnny221B/TAPS

0
View on GitHub↗
6 stars·0 forks·Python·MIT·10 views

TAPS

Time-Annealed Perturbation Sampling (TAPS) is an inference-time method for improving diversity in diffusion language models without sacrificing generation quality.

Features

  • Inference Optimization - Diverse generation via time-annealed perturbation sampling.

Star history

Star history chart for johnny221b/tapsStar history chart for johnny221b/taps

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Open-source alternatives to TAPS

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  • conzel/super-outlier-dlmConzel avatar

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Frequently asked questions

What does johnny221b/taps do?

Time-Annealed Perturbation Sampling (TAPS) is an inference-time method for improving diversity in diffusion language models without sacrificing generation quality.

What are the main features of johnny221b/taps?

The main features of johnny221b/taps are: Inference Optimization.

What are some open-source alternatives to johnny221b/taps?

Open-source alternatives to johnny221b/taps include: crys-chen/dpad — Efficiency: DPad-enhanced dLLMs achieve up to a 61.39× speedup over vanilla dLLM baselines. Accuracy: DPad-enhanced… cychomatica/freedave — Free Draft-and-Verification: Toward Lossless Parallel Decoding for Diffusion Large Language Models. czg1225/dmax — DMax is a new dLLM paradigm achieving aggressive parallel decoding while preserving generation quality. danielmisrael/apd — Official repository for the paper: Accelerating Diffusion LLMs via Adaptive Parallel Decoding. duterscmy/soar —        . conzel/super-outlier-dlm — Code accompanying the paper "Layer Collapse in Diffusion Language Models" by Alexander Conzelmann, Albert…