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Towards Looped Models Done Right, Part II: Rethinking at Fixed Points
Benhao Huang, Chufan Shi, Junlin Chen +4
Every recurrence of a looped language model adds cost in training, decoding, prefill, and reinforcement learning (RL). The closer recurrent states get to fixed points, the less the…
Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning
Benhao Huang, Zhengyang Geng, Zico Kolter
Scaling test-time compute by iteratively updating a latent state has emerged as a powerful paradigm for reasoning. Yet the internal mechanisms that enable these iterative models to…
Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments
Hansen Jin Lillemark, Benhao Huang, Fangneng Zhan +2
Embodied systems experience the world as 'a symphony of flows': a combination of many continuous streams of sensory input coupled to self-motion, interwoven with the dynamics of ex…