3 citations · 9 across the 9 of their papers we have counts for
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cs.CL2023
How Well Do Text Embedding Models Understand Syntax?
Yan Zhang, Zhaopeng Feng, Zhiyang Teng +2
Text embedding models have significantly contributed to advancements in natural language processing by adeptly capturing semantic properties of textual data. However, the ability o…
cs.CL2023★ 3 cited
Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models
Tingyu Xie, Qi Li, Yan Zhang +2
Exploring the application of powerful large language models (LLMs) on the named entity recognition (NER) task has drawn much attention recently. This work pushes the performance bo…
cs.CL2023★ 3 cited
Empirical Study of Zero-Shot NER with ChatGPT
Tingyu Xie, Qi Li, Jian Zhang +3
Large language models (LLMs) exhibited powerful capability in various natural language processing tasks. This work focuses on exploring LLM performance on zero-shot information ext…