Beyond One-Size-Fits-All: Multi-Domain, Multi-Task Framework for Embedding Model Selection

Abstract

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.