4 papers
BERT-based Models vs. Large Language Models for Low-Resource Named Entity Recognition: A Comparative Study on Marathi
Hariom Ingle, Ronit Ghode, Ishwari Gondkar +2
Named Entity Recognition (NER) for low-resource languages such as Marathi remains a challenging task due to limited annotated resources and linguistic complexity. Although recent L…
MahaParaphrase: A Marathi Paraphrase Detection Corpus and BERT-based Models
Suramya Jadhav, Abhay Shanbhag, Amogh Thakurdesai +3
Paraphrases are a vital tool to assist language understanding tasks such as question answering, style transfer, semantic parsing, and data augmentation tasks. Indic languages are c…
On Limitations of LLM as Annotator for Low Resource Languages
Suramya Jadhav, Abhay Shanbhag, Amogh Thakurdesai +2
Low-resource languages face significant challenges due to the lack of sufficient linguistic data, resources, and tools for tasks such as supervised learning, annotation, and classi…
Non-Contextual BERT or FastText? A Comparative Analysis
Abhay Shanbhag, Suramya Jadhav, Amogh Thakurdesai +2
Natural Language Processing (NLP) for low-resource languages, which lack large annotated datasets, faces significant challenges due to limited high-quality data and linguistic reso…