Large Language Models are Few-Shot Clinical Information Extractors

Large Language Models are Few-Shot Clinical Information Extractors

25 May 2022

Papers citing "Large Language Models are Few-Shot Clinical Information Extractors"

9 / 9 papers shown

Title
BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text Jiageng Wu Bowen Gu Ren Zhou Kevin Xie Doug Snyder ... S. Jonathan H. Chen Santiago Romero-Brufau K. J. Lin Jie Yang LM&MA ELM 72 0 0 28 Apr 2025
Instruction Induction: From Few Examples to Natural Language Task Descriptions Or Honovich Uri Shaham Samuel R. Bowman Omer Levy ELM LRM 102 110 0 22 May 2022
What GPT Knows About Who is Who Xiaohan Yang Eduardo Peynetti Vasco Meerman Christy Tanner 109 8 0 16 May 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 292 8,441 0 04 Mar 2022
Co-training Improves Prompt-based Learning for Large Language Models Hunter Lang Monica Agrawal Yoon Kim David Sontag VLM LRM 132 35 0 02 Feb 2022
Multitask Prompted Training Enables Zero-Shot Task Generalization Victor Sanh Albert Webson Colin Raffel Stephen H. Bach Lintang Sutawika ... T. Bers Stella Biderman Leo Gao Thomas Wolf Alexander M. Rush LRM 200 1,436 0 15 Oct 2021
On Generalization in Coreference Resolution Shubham Toshniwal Patrick Xia Sam Wiseman Karen Livescu Kevin Gimpel 97 33 0 20 Sep 2021
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages Peng Qi Yuhao Zhang Yuhui Zhang Jason Bolton Christopher D. Manning AI4TS 170 1,456 0 16 Mar 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 235 1,382 0 21 Jan 2020