Amazon SR
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VirtualMLE: A Virtual ML Engineer that Optimizes Sequential Recommenders
arXiv:2606.03221v1 Announce Type: new Abstract: Recent advancements in Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning, reflection, and tool utilization, unlocking new paradigms for automating complex engineering workflows. However, in the domain of sequential recommendation (SR), tuning models on new datasets still relies heavily on the manual trial-and-error of experienced machine learning engineers. To bridge this gap, we propose \textbf{VirtualMLE}, an...