FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural
Language Understanding

FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding

27 September 2021

Ming Ding

Ruslan Salakhutdinov

Sebastian Ruder

Papers citing "FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding"

9 / 9 papers shown

Title
FLEX: Unifying Evaluation for Few-Shot NLP Jonathan Bragg Arman Cohan Kyle Lo Iz Beltagy 177 93 0 15 Jul 2021
CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP Qinyuan Ye Bill Yuchen Lin Xiang Ren 194 167 0 18 Apr 2021
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 254 882 0 18 Apr 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 267 2,999 0 18 Apr 2021
What Makes Good In-Context Examples for GPT- $3$ ? Jiachang Liu Dinghan Shen Yizhe Zhang Bill Dolan Lawrence Carin Weizhu Chen AAML RALM 258 991 0 17 Jan 2021
Free Lunch for Few-shot Learning: Distribution Calibration Shuo Yang Lu Liu Min Xu OODD 181 287 0 16 Jan 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 225 1,649 0 31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 233 1,382 0 21 Jan 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 278 6,003 0 20 Apr 2018