Learning Multi-Indicator Weights for Data Selection: A Joint Task-Model Adaptation Framework with Efficient Proxies

ArXi:2605.09665v1 Announce Type: cross Data selection is a key component of efficient instruction tuning for large language models, as recent work has shown that data quality often matters than data quantity. Accordingly, prior studies have