AcquisitionSynthesis: Targeted Data Generation using Acquisition Functions

ArXi:2605.13149v1 Announce Type: cross Data quality remains a critical bottleneck in developing capable, competitive models. Researchers have explored many ways to generate top quality samples. Some works rely on rejection sampling: generating lots of synthetic samples and filtering out low-quality samples. Other works rely on larger or closed-source models to extract model weaknesses, necessary skills, or a curriculum off of which to base data generation.