---
id: 20260918-T0-09
title: "DANTINOX统一三种语言生成范式，方便直接对比"
title_en: "DANTINOX Unifies Autoregressive, Diffusion, and Flow-Matching Language Models"
url: https://ai.daily.yangsir.net/daily/20260918-T0-09
issue_date: 2026-09-18
publish_date: 2026-09-17T04:00:00.000Z
category: research
source_name: "arXiv cs.CL (NLP)"
source_url: https://arxiv.org/abs/2609.17535
---

# DANTINOX统一三种语言生成范式，方便直接对比

arXiv论文提出DANTINOX，一个统一框架，把自回归解码、离散掩码扩散和连续流匹配三种语言生成范式整合到同一代码库中。此前这三种方法各自独立实现，导致对比结果常因代码差异而不可靠。DANTINOX让研究者在相同条件下测量不同范式的表现差异，减少实现细节带来的干扰。这对需要选型语言生成架构的研究和工程团队有直接参考价值。

## English Version

**DANTINOX Unifies Autoregressive, Diffusion, and Flow-Matching Language Models**

A new arXiv paper introduces DANTINOX, a unified framework that integrates three language generation paradigms -- autoregressive decoding, discrete masked diffusion, and continuous flow-matching -- into a single codebase. Previously each lived in separate implementations, making comparisons unreliable due to code differences. DANTINOX lets researchers measure performance differences under identical conditions, reducing noise from implementation details. This is directly useful for teams choosing a language generation architecture.

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**来源**：[arXiv cs.CL (NLP)](https://arxiv.org/abs/2609.17535)

**详情页**：https://ai.daily.yangsir.net/daily/20260918-T0-09

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