Unveiling the Multi-Annotation Process: Examining the Influence of Annotation Quantity and Instance Difficulty on Model Performance

23 October 2023

Papers citing "Unveiling the Multi-Annotation Process: Examining the Influence of Annotation Quantity and Instance Difficulty on Model Performance"

6 / 6 papers shown

Title
Model Hubs and Beyond: Analyzing Model Popularity, Performance, and Documentation Pritam Kadasi Sriman Reddy Srivathsa Vamsi Chaturvedula Rudranshu Sen Agnish Saha Soumavo Sikdar Sayani Sarkar Suhani Mittal Rohit Jindal Mayank Singh 53 0 0 19 Mar 2025
Context Does Matter: Implications for Crowdsourced Evaluation Labels in Task-Oriented Dialogue Systems Clemencia Siro Mohammad Aliannejadi Maarten de Rijke 35 3 0 15 Apr 2024
Corpus Considerations for Annotator Modeling and Scaling O. O. Sarumi Béla Neuendorf Joan Plepi Lucie Flek Jorg Schlotterer Charles F Welch 38 1 0 02 Apr 2024
$Understanding Dataset Difficulty with $\mathcal{V}$-Usable Information$ Understanding Dataset Difficulty with $\mathcal{V}$ -Usable Information Kawin Ethayarajh Yejin Choi Swabha Swayamdipta 167 157 0 16 Oct 2021
Clean or Annotate: How to Spend a Limited Data Collection Budget Derek Chen Zhou Yu Samuel R. Bowman 35 13 0 15 Oct 2021
Pre-train or Annotate? Domain Adaptation with a Constrained Budget Fan Bai Alan Ritter Wei-ping Xu 66 31 0 10 Sep 2021