Identifying Semantically Difficult Samples to Improve Text Classification

13 February 2023

Papers citing "Identifying Semantically Difficult Samples to Improve Text Classification"

9 / 9 papers shown

Title
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics Swabha Swayamdipta Roy Schwartz Nicholas Lourie Yizhong Wang Hannaneh Hajishirzi Noah A. Smith Yejin Choi 142 452 0 22 Sep 2020
SemEval-2016 Task 4: Sentiment Analysis in Twitter Preslav Nakov Alan Ritter Sara Rosenthal Fabrizio Sebastiani Veselin Stoyanov 69 341 0 03 Dec 2019
Data Valuation using Reinforcement Learning Jinsung Yoon Sercan O. Arik Tomas Pfister TDI 91 182 0 25 Sep 2019
Improving Neural Conversational Models with Entropy-Based Data Filtering Richard Csaky Patrik Purgai Gábor Recski 95 58 0 14 May 2019
Data Shapley: Equitable Valuation of Data for Machine Learning Amirata Ghorbani James Zou TDI FedML 99 791 0 05 Apr 2019
Evolutionary Data Measures: Understanding the Difficulty of Text Classification Tasks Edward Collins Nikolai Rozanov M. Kaptein 70 29 0 05 Nov 2018
Automated Hate Speech Detection and the Problem of Offensive Language Thomas Davidson Dana Warmsley M. Macy Ingmar Weber 81 2,704 0 11 Mar 2017
Enriching Word Vectors with Subword Information Piotr Bojanowski Edouard Grave Armand Joulin Tomas Mikolov NAI SSL VLM 234 9,991 0 15 Jul 2016
Efficient Estimation of Word Representations in Vector Space Tomas Mikolov Kai Chen G. Corrado J. Dean 3DV 701 31,571 0 16 Jan 2013