ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER

29 May 2023

Papers citing "ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER"

7 / 7 papers shown

Title
Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges Farid Ariai Gianluca Demartini ELM AILaw VLM 40 4 0 25 Oct 2024
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 238 805 0 14 Oct 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,844 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,918 0 31 Dec 2020
Contrastive Representation Learning: A Framework and Review Phúc H. Lê Khắc Graham Healy A. Smeaton SSL AI4TS 164 684 0 10 Oct 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,587 0 21 Jan 2020
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 413 2,584 0 03 Sep 2019