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STEPQuant: When and Where Errors Matter in Delta-Rule Recurrent State Quantization

96 upvotes · 29 SEP 2026 · Bingchen Yao, Haobo Xu, Haokun Lin et al.

This paper proposes a method to quantize recurrent states in deep learning models more efficiently, reducing memory usage without sacrificing accuracy. Practitioners might care about this research if they need to optimize memory usage in their models.

recurrent state quantizationdelta-rule modelslow-precision arithmeticmemory efficiencyGPU optimization