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Reasoning with Continuous Latent Diffusion

Paper recorded by Signals 4 on 2026-09-28 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-28 on arXiv · recorded by Signals 4 on 2026-09-29

Category: cs.AI · 人工智能 · first seen 2026-09-29

Abstract

Continuous diffusion generates complete reasoning solutions through iterative refinement in latent space. We introduce Latent Flow Reasoning Models (LFRMs), an ELF-based training and inference recipe. Our experiments show that accurate decoding alone does not ensure strong reasoning performance. We therefore learn compact representations from multiple layers of a strong autoregressive teacher. The

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#15 most recent of 440 cs.AI papers we have recorded · ↑ newer: Distillation Defenses Easily Break After Reinforcement Learning · ↓ older: Report: Progressive Disclosure of Agent Skills
Cite this page: Reasoning with Continuous Latent Diffusion: the #15 most recent of 440 cs.AI papers we have recorded (as of 2026-09-28). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/reasoning-with-continuous-latent-diffusion.html
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