Enhancing Essay Scoring: An Analytical and Holistic Approach With Few-Shot Transformer-Based Models

Enhancing Essay Scoring: An Analytical and Holistic Approach With Few-Shot Transformer-Based Models

In the field of automated essay scoring (AES), the task of evaluating written compositions has been a persistent challenge. Despite the impressive capabilities of generalized transformer models in various natural language processing (NLP) domains, their application to essay scoring has often fallen...

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Xehetasun bibliografikoak
Egile Nagusiak: Tahira Amin, Zahoor-Ur-Rehman Tanoli, Farhan Aadil, Khalid Mahmood Awan, Sangsoon Lim
Formatua: Artikulua
Hizkuntza:English
Argitaratua: IEEE 2025-01-01
Saila:IEEE Access
Gaiak:
AES
NLP
transfer learning
BERT
few-shot learning
holistic scoring
Sarrera elektronikoa:https://ieeexplore.ieee.org/document/10843186/

Internet

https://ieeexplore.ieee.org/document/10843186/

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