<p>AI research agents can propose far more experiments than they can afford to run. Meta FAIR, Oxford and UCL introduce AI Research Preference Models — frozen LLM judges that rank 15 unexecuted candidates and execute only one. On AIRS-Bench, the average normalized score rises from 0.684 to 0.729, and the baseline's 24-hour result arrives in roughly 15 hours.</p>
<p>The post <a href="https://www.marktechpost.com/2026/09/06/meta-fair-introduces-ai-research-preference-models-rpms-ranking-ml-experiments-before-spending-gpu-hours/">Meta FAIR Introduces AI Research Preference Models (RPMs): Ranking ML Experiments Before Spending GPU Hours</a> appeared first on <a href="https://www.marktechpost.com">MarkTechPost</a>.</p>