Hybrid Approach to Automated Essay Scoring: Integrating Deep Learning Embeddings with Handcrafted Linguistic Features for Improved Accuracy

Automated Essay Scoring (AES) systems face persistent challenges in delivering accuracy and efficiency in evaluations. This study introduces an approach that combines embeddings generated using RoBERTa with handcrafted linguistic features, leveraging Lightweight XGBoost (LwXGBoost) for enhanced scor...

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Bibliografske podrobnosti

Principais autores:	Muhammad Faseeh, Abdul Jaleel, Naeem Iqbal, Anwar Ghani, Akmalbek Abdusalomov, Asif Mehmood, Young-Im Cho
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2024-10-01
Serija:	Mathematics
Teme:	automated essay scoring RoBERTa embeddings handcrafted features LwXGBoost RoBERTa
Online dostop:	https://www.mdpi.com/2227-7390/12/21/3416
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