17 citations · 24 across the 4 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
cs.CL2024
Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks
R. Patrick Xian, Alex J. Lee, Satvik Lolla +4
The increasing depth of parametric domain knowledge in large language models (LLMs) is fueling their rapid deployment in real-world applications. Understanding model vulnerabilitie…
cs.CL2021★ 7 cited
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding
Yanan Zheng, Jing Zhou, Yujie Qian +7
The few-shot natural language understanding (NLU) task has attracted much recent attention. However, prior methods have been evaluated under a disparate set of protocols, which hin…
cs.CL2021★ 17 cited
FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning
Jing Zhou, Yanan Zheng, Jie Tang +2
Most previous methods for text data augmentation are limited to simple tasks and weak baselines. We explore data augmentation on hard tasks (i.e., few-shot natural language underst…