Qwen

The AI industry is seeing a surge in 'model routers' designed to intelligently distribute LLM queries to the most cost-effective and capable models. Companies including Cursor, Ramp, and Meta are developing these systems to optimize performance and reduce the high costs associated with frontier-grade models.

This technical repository presents SRM-LoRA, a novel approach designed to minimize hallucinations in LLMs via specialized metric updates. The research demonstrates superior performance compared to standard LoRA techniques across various ablation studies.

This paper presents a method for converting pretrained transformers into linear-time architectures by focusing on the efficiency of state update designs. By analyzing softmax attention through a first-order approximation, the authors prove that delta-style updates are superior for post hoc linearization.

This paper presents a method for converting pretrained transformers into linear-time architectures by focusing on the efficiency of state update designs. By analyzing softmax attention through a first-order approximation, the authors prove that delta-style updates are superior for post hoc linearization.