Beyond One-Size-Fits-All: Multi-Domain, Multi-Task Framework for Embedding Model Selection
<|reference_start|>Beyond One-Size-Fits-All: Multi-Domain, Multi-Task Framework for Embedding Model Selection: This position paper proposes a systematic approach towards developing a framework to help select the most effective embedding models for natural language processing (NLP) tasks, addressing the challenge posed by the proliferation of both proprietary and open-source encoder models.<|reference_end|>
@article{khetan2024beyond,
    title={Beyond One-Size-Fits-All: Multi-Domain, Multi-Task Framework for
  Embedding Model Selection},
    author={Vivek Khetan},
    journal={arXiv preprint arXiv:2404.00458},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.00458},
    primaryClass={cs.CL cs.IR}
}