38 citations · 46 across the 6 of their papers we have counts for
6 papers
How far is Language Model from 100% Few-shot Named Entity Recognition in Medical Domain
Mingchen Li, Rui Zhang
Recent advancements in language models (LMs) have led to the emergence of powerful models such as Small LMs (e.g., T5) and Large LMs (e.g., GPT-4). These models have demonstrated e…
NameRec*: Highly Accurate and Fine-grained Person Name Recognition
Rui Zhang, Yimeng Dai, Shijie Liu
In this paper, we introduce the NameRec* task, which aims to do highly accurate and fine-grained person name recognition. Traditional Named Entity Recognition models have good perf…
Prototypical Representation Learning for Relation Extraction
Ning Ding, Xiaobin Wang, Yao Fu +7
Recognizing relations between entities is a pivotal task of relational learning. Learning relation representations from distantly-labeled datasets is difficult because of the abund…
Entity Extraction with Knowledge from Web Scale Corpora
Zeyi Wen, Zeyu Huang, Rui Zhang
Entity extraction is an important task in text mining and natural language processing. A popular method for entity extraction is by comparing substrings from free text against a di…
A Technical Report: Entity Extraction using Both Character-based and Token-based Similarity
Zeyi Wen, Dong Deng, Rui Zhang +1
Entity extraction is fundamental to many text mining tasks such as organisation name recognition. A popular approach to entity extraction is based on matching sub-string candidates…
Cruciform: Solving Crosswords with Natural Language Processing
Dragomir Radev, Rui Zhang, Steve Wilson +8
Crossword puzzles are popular word games that require not only a large vocabulary, but also a broad knowledge of topics. Answering each clue is a natural language task on its own a…