3 accepted papers
Efficient resume parsing is critical for global hiring, yet the absence of dedicated benchmarks for evaluating large language models (LLMs) on multilingual, structure-rich resumes hinders progress. To address this, we introduce ResumeBench, the first privacy-compliant benchmark comprising 2,500 synt
Domain generalization studies the problem of training a model with samples from several domains (or distributions) and then testing the model with samples from a new, unseen domain. In this paper, we propose a novel approach for domain generalization that leverages recent advances in large vision-la…
When facing changing environments in the real world, the lightweight model on client devices suffer from severe performance drop under distribution shifts. The main limitations of existing device model lie in: (1) unable to update due to the computation limit of the device, (2) limited generalizatio…