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Liliang Ren

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#machine learning May 2026

Latent Recurrent Transformer: Architecture Exploration, Training Strategies, and Scaling Behavior

Latent Recurrent Transformer is studied, a lightweight augmentation of autoregressive transformers that reuses a high-level source-layer hidden state from the previous token as recurrent memory for the next token, while retaining one-forward-per-token decoding with 9% latency overhead over the standard Transformer.

Zeyi Huang, Xuehai He, Liliang Ren et al. · arXiv.org · 2 citations