Towards Robust and Generalizable Training: An Empirical Study of Noisy
Slot Filling for Input Perturbations

Towards Robust and Generalizable Training: An Empirical Study of Noisy Slot Filling for Input Perturbations

5 October 2023

Weiran Xu

Papers citing "Towards Robust and Generalizable Training: An Empirical Study of Noisy Slot Filling for Input Perturbations"

4 / 4 papers shown

Title
Evaluating Concurrent Robustness of Language Models Across Diverse Challenge Sets Vatsal Gupta Pranshu Pandya Tushar Kataria Vivek Gupta Dan Roth AAML 51 1 0 03 Jan 2025
Revisit Input Perturbation Problems for LLMs: A Unified Robustness Evaluation Framework for Noisy Slot Filling Task Guanting Dong Jinxu Zhao Tingfeng Hui Daichi Guo Wenlong Wan ... Yueyan Qiu Zhuoma Gongque Keqing He Zechen Wang Weiran Xu AAML 27 19 0 10 Oct 2023
Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot Filling Liwen Wang Xuefeng Li Jiachi Liu Keqing He Yuanmeng Yan Weiran Xu VLM 44 24 0 07 Oct 2021
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 243 7,597 0 03 Jul 2012