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News/The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check
arxiv
PublishedApril 27, 2026 at 4:00 AM
▼bearish

The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check

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arxiv.orgfull article ↗
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Publisher summary· verbatim

arXiv:2601.12979v3 Announce Type: replace Abstract: The pursuit of real-time agentic interaction has driven interest in Diffusion-based Large Language Models (dLLMs) as alternatives to auto-regressive backbones, promising to break the sequential latency bottleneck. However, does such efficiency gain

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Discussion
Mentioned models
02
  • 01
    LLaDA
  • 02
    Dream
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#diffusion-based#language-models#agentic-interaction#evaluation

No replies yet. Be first.

Mentioned models
02
  • 01
    LLaDA
  • 02
    Dream
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#diffusion-based#language-models#agentic-interaction#evaluation
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Originally published on arxiv ↗
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