Author

Qi-Zhen Lan

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#artificial intelligence Preprint Sep 2026

You Cannot Pick a Provider From the Price List: Market-Aware Routing for Open-Weight LLM Inference

Existing LLM routers choose among models using static per-model costs. We show that open-weight inference markets introduce a second, largely ignored decision axis: after choosing a model, a client must still choose which provider serves it. Measuring live endpoints across [nummodels] open models, competing providers,...

Liang He, Jing Wen, Yi-Xiong Chen et al. · 0 citations

#machine learning Preprint Sep 2026

EvoTreeNAD: Genealogy-Guided Evolution for LLM-Driven Neural Architecture Discovery

EvoTreeNAD is introduced, a genealogy-guided evolutionary algorithm that constructs trainable architectures without a supplied seed or a hand-specified search space that outperforms direct generation, best-of-$N$ greedy continuation, and full-family-mean routing.

Li-Shan Yu, D. Jiu, Qi-Zhen Lan et al. · 0 citations

Open access Aug 2026

PerturbLDM: conditional latent diffusion for modelling single-cell perturbation responses

PerturbLDM, a latent-diffusion framework for conditional generation of single-cell transcriptional responses, is introduced, showing support for conditional response generation across data scales and biological settings.

Li-Shan Yu, Kang-Lin Hsieh, Y. Chu et al. · bioRxiv · 0 citations