作者位次 #4/5ACL 2026Findings· Findings of ACL
Scaling Performance and Low-Resource Annotation with Many-Shot In-Context Learning for Named Entity Recognition
Qi Zhang · Fangping Lan · Cornelia Caragea · Longin Jan Latecki · Eduard Dragut
摘要
In-context learning (ICL) with large language models (LLMs) has emerged as a powerful alternative to fine-tuning for Named Entity Recognition (NER), achieving strong performance with minimal annotation and no additional training. However, prior work has shown that despite their adaptability, LLMs...