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DeMoP: A Language-Model-Guided Mixture-of-Experts Framework for Cancer Prognosis

Integrating heterogeneous clinical and molecular data for cancer prognosis remains challenging because their dimensionality, semantics and distributions differ across patients and cohorts. Here we present DeMoP, a language-model-guided mixture-of-experts framework that serializes structured patient profiles as natural-language sequences and learns adaptive prognostic representations from clinical…

We haven't written up this one. bioRxiv has the full story — the link below goes straight to it.

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Qwen3.8-Flash-Next

Qwen3.8-Flash-Next Another open weights model from Qwen. This one is "a multimodal MoE model that also serves as an early preview of the architecture used in Qwen4".

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