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"

9 / 9 papers shown

Title
Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models Oshin Agarwal Yinfei Yang Byron C. Wallace A. Nenkova 40 23 0 08 Apr 2020
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study Jinlan Fu Pengfei Liu Qi Zhang Xuanjing Huang AI4CE 50 73 0 12 Jan 2020
A Survey on Recent Advances in Named Entity Recognition from Deep Learning models Vikas Yadav Steven Bethard 3DV 52 592 0 25 Oct 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.3K 94,479 0 11 Oct 2018
Deep contextualized word representations Matthew E. Peters Mark Neumann Mohit Iyyer Matt Gardner Christopher Clark Kenton Lee Luke Zettlemoyer NAI 156 11,541 0 15 Feb 2018
Generalisation in Named Entity Recognition: A Quantitative Analysis Isabelle Augenstein Leon Derczynski Kalina Bontcheva 35 114 0 11 Jan 2017
Neural Architectures for Named Entity Recognition Guillaume Lample Miguel Ballesteros Sandeep Subramanian Kazuya Kawakami Chris Dyer 217 4,007 0 04 Mar 2016
Bidirectional LSTM-CRF Models for Sequence Tagging Zhiheng Huang Wenyuan Xu Kai Yu 171 4,017 0 09 Aug 2015
Natural Language Processing (almost) from Scratch R. Collobert Jason Weston Léon Bottou Michael Karlen Koray Kavukcuoglu Pavel P. Kuksa 151 7,721 0 02 Mar 2011