Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve

9 April 2020

Papers citing "Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve"

7 / 7 papers shown

Title
Influence Functions for Sequence Tagging Models Sarthak Jain Varun Manjunatha Byron C. Wallace A. Nenkova TDI 40 8 0 25 Oct 2022
Temporal Effects on Pre-trained Models for Language Processing Tasks Oshin Agarwal A. Nenkova VLM 30 53 0 24 Nov 2021
LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Prompting Xiang Chen Lei Li Shumin Deng Chuanqi Tan Changliang Xu Fei Huang Luo Si Huajun Chen Ningyu Zhang VLM 42 65 0 31 Aug 2021
Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition Abbas Ghaddar Philippe Langlais Ahmad Rashid Mehdi Rezagholizadeh 44 43 0 24 Jul 2021
How Do Your Biomedical Named Entity Recognition Models Generalize to Novel Entities? Hyunjae Kim Jaewoo Kang AI4CE 94 21 0 01 Jan 2021
Unsupervised Data Augmentation with Naive Augmentation and without Unlabeled Data David Lowell Brian Howard Zachary Chase Lipton Byron C. Wallace 32 23 0 22 Oct 2020
FLAT: Chinese NER Using Flat-Lattice Transformer Xiaonan Li Hang Yan Xipeng Qiu Xuanjing Huang 44 390 0 24 Apr 2020