Peijia Qin — accepted AI-conference papers

2026

Models Under SCOPE: Scalable and Controllable Routing via Pre-hoc Reasoning

Qi Cao, Shuhao Zhang, Ruizhe Zhou, Ruiyi Zhang, Peijia Qin, Pengtao Xie

ICML 2026poster

Model routing chooses which language model to use for each query. By sending easy queries to cheaper models and hard queries to stronger ones, it can significantly reduce inference cost while maintaining high accuracy. However, most existing routers treat this as a fixed choice among a small set of …

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2025

Learning to Quantize for Training Vector-Quantized Networks

Peijia Qin, Jianguo Zhang

ICML 2025poster

Deep neural networks incorporating discrete latent variables have shown significant potential in sequence modeling. A notable approach is to leverage vector quantization (VQ) to generate discrete representations within a codebook. However, its discrete nature prevents the use of standard backpropaga…

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