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05/23/2023
Active Learning Principles for In-Context Learning with Large Language Models
The remarkable advancements in large language models (LLMs) have signifi...
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05/21/2023
On the Limitations of Simulating Active Learning
Active learning (AL) is a human-and-model-in-the-loop paradigm that iter...
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02/23/2023
Dynamic Benchmarking of Masked Language Models on Temporal Concept Drift with Multiple Views
Temporal concept drift refers to the problem of data changing over time....
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02/14/2023
Investigating Multi-source Active Learning for Natural Language Inference
In recent years, active learning has been successfully applied to an arr...
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03/18/2022
Challenges and Strategies in Cross-Cultural NLP
Various efforts in the Natural Language Processing (NLP) community have ...
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09/08/2021
Active Learning by Acquiring Contrastive Examples
Common acquisition functions for active learning use either uncertainty ...
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09/04/2021
Frustratingly Simple Pretraining Alternatives to Masked Language Modeling
Masked language modeling (MLM), a self-supervised pretraining objective,...
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04/16/2021
Bayesian Active Learning with Pretrained Language Models
Active Learning (AL) is a method to iteratively select data for annotati...
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09/28/2020
Domain Adversarial Fine-Tuning as an Effective Regularizer
In Natural Language Processing (NLP), pre-trained language models (LMs) ...
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06/09/2019
