Picuslab-DIETI

Picuslab-DIETI is happy to share its last publication entitled "TaughtNet: Learning Multi-Task Biomedical Named Entity Recognition From Single-Task Teachers" - whose authors are Vincenzo Moscato, Marco Postiglione, Carlo Sansone and Giancarlo Sperlì - has been accepted on IEEE Journal of Biomedical and Health Informatics.

In this work, we propose TaughtNet , a knowledge distillation-based framework allowing us to fine-tune a single multi-task student model by leveraging both the ground truth and the knowledge of single-task teachers .

TaughtNet: Learning Multi-Task Biomedical Named Entity Recognition From Single-Task Teachers In Biomedical Named Entity Recognition (BioNER), the use of current cutting-edge deep learning-based methods, such as deep bidirectional transformers (e.g. BERT, GPT-3), can be substantially hampered by the absence of publicly accessible annotated datasets. When the BioNER system is required to anno...