Author

Shicheng Wen

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#machine learning Preprint Oct 2026

Towards Looped Models Done Right, Part I: Topology, Input Injection, Recurrent-State Design

Looped language models reuse physical Transformer blocks across logical depth, but established architectures entangle recurrence placement, input injection, and recurrent state organization. We isolate these axes in models trained from scratch at matched parameter scale, logical depth, and token budgets, and then test...

Benhao Huang, Chu-Fan Shi, Jun-Lin Chen et al. · 4 citations

#machine learning Preprint Oct 2026

Towards Looped Models Done Right, Part II: Rethinking at Fixed Points

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 path to them matters. This enables truncated backpropagation in training; terminal key-value (KV) sharing for decoding with almost no loss...

Benhao Huang, Chu-Fan Shi, Jun-Lin Chen et al. · 1 citation

Preprint Jul 2026

Plover: Steering GUI Agents through Plan-Centric Interaction

This work presents Plover, a plan-centric vision-based GUI automation system that externalizes task plans and replanning as persistent, inspectable, and revisable artifacts and shows that many autonomous GUI-agent failures are structurally repairable when plans remain visible and interventions are localized.

M. Venkatesan, Shicheng Wen, Jiajing Guo et al. · 1 citation