Why Comparing Single Performance Scores Does Not Allow to Draw Conclusions About Machine Learning Approaches

26 March 2018

Papers citing "Why Comparing Single Performance Scores Does Not Allow to Draw Conclusions About Machine Learning Approaches"

11 / 11 papers shown

Title
Collaboration or Corporate Capture? Quantifying NLP's Reliance on Industry Artifacts and Contributions Will Aitken Mohamed Abdalla K. Rudie Catherine Stinson 33 0 0 06 Dec 2023
Context-aware attention layers coupled with optimal transport domain adaptation and multimodal fusion methods for recognizing dementia from spontaneous speech Loukas Ilias D. Askounis 34 9 0 25 May 2023
Drawing Causal Inferences About Performance Effects in NLP Sandra Wankmüller CML 16 1 0 14 Sep 2022
A Comparison of Approaches for Imbalanced Classification Problems in the Context of Retrieving Relevant Documents for an Analysis Sandra Wankmüller 33 2 0 03 May 2022
What do we Really Know about State of the Art NER? Sowmya Vajjala Ramya Balasubramaniam 27 15 0 29 Apr 2022
SkillSpan: Hard and Soft Skill Extraction from English Job Postings Mike Zhang Kristian Nørgaard Jensen Sif Dam Sonniks Barbara Plank 28 53 0 27 Apr 2022
deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks Dennis Ulmer Christian Hardmeier J. Frellsen 48 42 0 14 Apr 2022
Cartography Active Learning Mike Zhang Barbara Plank 27 37 0 09 Sep 2021
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks Nils Reimers Iryna Gurevych 81 11,735 0 27 Aug 2019
Classification and Clustering of Arguments with Contextualized Word Embeddings Nils Reimers Benjamin Schiller Tilman Beck Johannes Daxenberger Christian Stab Iryna Gurevych 14 165 0 24 Jun 2019
Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification Junjie Zeng Yue Hu 14 32 0 05 Nov 2018