DiffResearch: Accelerating Deep Research with Diffusion Language Models
Read the original on arXiv AI →DiffResearch is an open multi‑agent deep research framework that replaces the traditional autoregressive language model backbone with a diffusion language model (dLLM) across all stages of research, from planning to writing. In experiments on 100 Deep Research Bench tasks, the diffusion backbone achieves roughly six times faster end‑to‑end latency, largely due to significant speedups in planning and long‑form generation. The framework also introduces dFast, a decomposition mode that reads intermediate denoising states to generate subqueries, yielding a median 1.99× speedup without compromising report quality and achieving the best overall score on the RACE rubric. whyItMatters":"The study demonstrates that diffusion language models can dramatically reduce latency in deep research systems, enabling faster interactive use while maintaining or improving output quality."
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