Robust Text Classification: Analyzing Prototype-Based Networks

Downstream applications often require text classification models to be accurate and robust. While the accuracy of the state-of-the-art Language Models (LMs) approximates human performance, they often exhibit a drop in performance on noisy data found in the real world. This lack of robustness can be...

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Veröffentlicht in:	arXiv.org 2024-10
Hauptverfasser:	Sourati, Zhivar, Deshpande, Darshan, Ilievski, Filip, Gashteovski, Kiril, Saralajew, Sascha
Format:	Artikel
Sprache:	eng
Schlagworte:	Classification Computer vision Human performance Modular design Perturbation Prototypes Robustness Text categorization
Online-Zugang:	Volltext
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