LLMaAA: Making Large Language Models as Active Annotators

30 October 2023

Papers citing "LLMaAA: Making Large Language Models as Active Annotators"

9 / 59 papers shown

Title
Summarization as Indirect Supervision for Relation Extraction K. Lu I-Hung Hsu Wenxuan Zhou Mingyu Derek Ma Muhao Chen 63 51 0 19 May 2022
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 344 0 13 Oct 2021
Towards Zero-Label Language Learning Zirui Wang Adams Wei Yu Orhan Firat Yuan Cao SyDa 170 101 0 19 Sep 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 274 1,114 0 18 Apr 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 278 3,784 0 18 Apr 2021
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP Timo Schick Sahana Udupa Hinrich Schütze 257 374 0 28 Feb 2021
What Makes Good In-Context Examples for GPT- $3$ ? Jiachang Liu Dinghan Shen Yizhe Zhang Bill Dolan Lawrence Carin Weizhu Chen AAML RALM 275 1,296 0 17 Jan 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,898 0 31 Dec 2020
Cold-start Active Learning through Self-supervised Language Modeling Michelle Yuan Hsuan-Tien Lin Jordan L. Boyd-Graber 104 180 0 19 Oct 2020