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--- nlp:data_preparation [2021/04/29 09:51] – [Creating a Train/Dev/Test Split] jmflanig
+++ nlp:data_preparation [2023/06/15 07:36] (current) – external edit 127.0.0.1
@@ Line 11: / Line 11: @@
   * [[https://www.aclweb.org/anthology/P19-1267.pdf|Gorman & Bedrick 2019 - We need to talk about standard splits]] Bad paper, DO NOT USE.  See [[https://www.aclweb.org/anthology/2021.eacl-main.156.pdf|Søgaard 2020]] below.
   * [[https://www.aclweb.org/anthology/2021.eacl-main.156.pdf|Søgaard et al 2020 - We Need to Talk About Random Splits]] Finds that both random and standard splits reward overfitting the training data.
-  * [[https://arxiv.org/pdf/1908.07898.pdf|Geva 2019]] argues that test set annotators should be disjoint from training set annotators.
+  *   * [[https://arxiv.org/pdf/1908.07898.pdf|Geva et al 2019 - Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets]]  Argues that test set annotators should be disjoint from training set annotators.
@@ Line 18: / Line 18: @@
 ===== Related Pages =====
+  * [[ml:Data Cleaning and Validation]]
   * [[Dataset Creation]]
   * [[Language Identification]]