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Ming-Qian Yu

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#artificial intelligence Preprint Sep 2026

T-LoopFormer: Token-Level Elastic-Depth Looped Transformers for Latent Reasoning with Dynamic Routing

Looped Transformers have recently demonstrated strong performance in both reasoning and language tasks by reusing a shared set of parameters across multiple iterations, achieving parameter efficiency without sacrificing representational power. Besides, looped Transformers perform inference directly in the latent space...

Ming-Qian Yu, Wen-Peng Zhang, Shao-Bo Cui et al. · 0 citations

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