A Few-shot Approach to Resume Information Extraction via Prompts

20 September 2022

Papers citing "A Few-shot Approach to Resume Information Extraction via Prompts"

8 / 8 papers shown

Title
Deeper Insights Without Updates: The Power of In-Context Learning Over Fine-Tuning Qingyu Yin Xuzheng He Luoao Deng Chak Tou Leong Fan Wang Yanzhao Yan Xiaoyu Shen Qiang Zhang 42 2 0 07 Oct 2024
Challenges and Opportunities of NLP for HR Applications: A Discussion Paper Jochen L. Leidner Mark Stevenson 26 1 0 13 May 2024
Resume Information Extraction via Post-OCR Text Processing Selahattin Serdar Helli Senem Tanberk Sena Nur Cavsak 13 1 0 23 Jun 2023
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 238 808 0 14 Oct 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,858 0 18 Apr 2021
WARP: Word-level Adversarial ReProgramming Karen Hambardzumyan Hrant Khachatrian Jonathan May AAML 254 342 0 01 Jan 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 243 1,924 0 31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,589 0 21 Jan 2020