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Latent Reasoning in Continuous Space for Unified Multimodal Models

Paper recorded by Signals 4 on 2026-10-30 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-30 on arXiv · recorded by Signals 4 on 2026-11-02

Category: cs.LG · 机器学习 · first seen 2026-11-02

Abstract

Unified Multimodal Models (UMMs) achieve remarkable success on diverse multimodal understanding and generation tasks, yet they still struggle to effectively leverage language-based chain-of-thought reasoning for image generation. As a result, existing reasoning-augmented UMMs often fail to inherit the test-time scaling and fine-grained controllability observed in large language models. We attribut

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#49 most recent of 703 cs.LG papers we have recorded · ↑ newer: Detection Instead of Inversion: T1-T2 Microstructure Quantification Wi · ↓ older: Counting on Dummies: Privacy Amplification with Observable Counts and
Cite this page: Latent Reasoning in Continuous Space for Unified Multimodal Models: the #49 most recent of 703 cs.LG papers we have recorded (as of 2026-10-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/latent-reasoning-in-continuous-space-for-unified-multimodal-models.html
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