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Looped Transformers achieve parameter efficiency by repeatedly executing a shared block across recurrent loops. Each loop yields an intermediate representation decodable for the same next token, yet standard decoding discards earlier states. Because earlier loops embody less computation, recurrence inherently supplies...
A new method to guide flow matching models using the frozen internal states of an existing diffusion model to construct a guidance signal, which eliminates the need for an additional forward pass at inference time and provides a reliable path to ensure that the weak and strong model share similar dynamics.
This work presents SimpleDesign, an effective multi-modal protein design model trained directly in the data space that leverages a single-stage end-to-end objective that combines discrete cross-entropy for sequences and a regression objective for structures.
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