On the Limitations of Simulating Active Learning

21 May 2023

Papers citing "On the Limitations of Simulating Active Learning"

9 / 9 papers shown

Title
AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets Pietro Lesci Andreas Vlachos 31 2 0 08 Apr 2024
Aligning Large Language Models through Synthetic Feedback Sungdong Kim Sanghwan Bae Jamin Shin Soyoung Kang Donghyun Kwak Kang Min Yoo Minjoon Seo ALM SyDa 73 67 0 23 May 2023
Improving alignment of dialogue agents via targeted human judgements Amelia Glaese Nat McAleese Maja Trkebacz John Aslanides Vlad Firoiu ... John F. J. Mellor Demis Hassabis Koray Kavukcuoglu Lisa Anne Hendricks G. Irving ALM AAML 225 495 0 28 Sep 2022
Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned Deep Ganguli Liane Lovitt John Kernion Amanda Askell Yuntao Bai ... Nicholas Joseph Sam McCandlish C. Olah Jared Kaplan Jack Clark 218 441 0 23 Aug 2022
Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets Guy Hacohen Avihu Dekel D. Weinshall 116 81 0 06 Feb 2022
Analyzing Dynamic Adversarial Training Data in the Limit Eric Wallace Adina Williams Robin Jia Douwe Kiela 184 29 0 16 Oct 2021
Hitting the Target: Stopping Active Learning at the Cost-Based Optimum Zac Pullar-Strecker Katharina Dost E. Frank Jörg Simon Wicker 13 10 0 07 Oct 2021
Active Learning for Argument Strength Estimation Nataliia Kees Michael Fromm Evgeniy Faerman T. Seidl 19 5 0 23 Sep 2021
Cold-start Active Learning through Self-supervised Language Modeling Michelle Yuan Hsuan-Tien Lin Jordan L. Boyd-Graber 104 180 0 19 Oct 2020