Prompt Tuned Embedding Classification for Multi-Label Industry Sector Allocation

arXiv:2309.12075v3 Announce Type: replace
Abstract: Prompt Tuning is emerging as a scalable and cost-effective method to fine-tune Pretrained Language Models (PLMs), which are often referred to as Large Language Models (LLMs). This study benchmarks the performance and computational efficiency of Prompt Tuning and baselines for multi-label text classification. This is applied to the challenging task of classifying companies into an investment firm's proprietary industry taxonomy, supporting their thematic investment strategy. Text-to-text classification is frequently reported to outperform task-specific classification heads, …

arxiv classification cs.ai cs.cl embedding industry prompt sector type