AI RESEARCH
Solve the Loop: Attractor Models for Language and Reasoning
arXiv CS.AI
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ArXi:2605.12466v1 Announce Type: cross Looped Transformers offer a promising alternative to purely feed-forward computation by iteratively refining latent representations, improving language modeling and reasoning. Yet recurrent architectures remain unstable to train, costly to optimize and deploy, and constrained to small, fixed recurrence depths. We