Extensive experiments on benchmarks from different DG tasks demonstrate that LFME is consistently beneficial to the baseline and can achieve comparable performance to existing arts.

Evaluating large language models (LLMs) is challenging.

In addition to sequence-based approaches, structure-based encoders have emerged to leverage the 3D structural information of proteins.

While some adaptive experimental strategies exist for the identification of the single best subgroup, they commonly do not enable the identification of the best set of subgroups.