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Fangping Lan

ACL 2026×2强化学习与后训练评测与基准多语言与语言学数据与预训练检索与知识
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合作网络3
1 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #2/5ACL 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...

强化学习与后训练评测与基准多语言与语言学OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

Making Revisions Understandable: A Survey of Edit Intentions, Methods, and Applications

Fangping Lan · Qi Zhang · Eduard Dragut

摘要

Text revision is a core process in document creation, capturing how authors iteratively refine, reorganize, and improve written content. With the increasing availability of large-scale revision histories from platforms such as Wikipedia and arXiv, NLP research has begun to move beyond modeling wh...

数据与预训练检索与知识多模态OpenReview 项目页

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