OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning
D Qiao, Y Su, P Wang, J Ye, W Xie, Y Zhou… - arXiv preprint arXiv …, 2024 - arxiv.org
Large Language Models (LLMs) have played an important role in many fields due to their
powerful capabilities. However, their massive number of parameters leads to high …
powerful capabilities. However, their massive number of parameters leads to high …
Entity Decomposition with Filtering: A Zero-Shot Clinical Named Entity Recognition Framework
Clinical named entity recognition (NER) aims to retrieve important entities within clinical
narratives. Recent works have demonstrated that large language models (LLMs) can …
narratives. Recent works have demonstrated that large language models (LLMs) can …
Show Less, Instruct More: Enriching Prompts with Definitions and Guidelines for Zero-Shot NER
A Zamai, A Zugarini, L Rigutini, M Ernandes… - arXiv preprint arXiv …, 2024 - arxiv.org
Recently, several specialized instruction-tuned Large Language Models (LLMs) for Named
Entity Recognition (NER) have emerged. Compared to traditional NER approaches, these …
Entity Recognition (NER) have emerged. Compared to traditional NER approaches, these …
LTNER: Large Language Model Tagging for Named Entity Recognition with Contextualized Entity Marking
F Yan, P Yu, X Chen - arXiv preprint arXiv:2404.05624, 2024 - arxiv.org
The use of LLMs for natural language processing has become a popular trend in the past
two years, driven by their formidable capacity for context comprehension and learning …
two years, driven by their formidable capacity for context comprehension and learning …