134 citations · 546 across the 43 of their papers we have counts for
6 papers · 1 filter
My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models and Evaluation Benchmarks
Tanmay Chavan, Omkar Gokhale, Aditya Kane +2
The research on code-mixed data is limited due to the unavailability of dedicated code-mixed datasets and pre-trained language models. In this work, we focus on the low-resource In…
L3Cube-MahaSent-MD: A Multi-domain Marathi Sentiment Analysis Dataset and Transformer Models
Aabha Pingle, Aditya Vyawahare, Isha Joshi +2
The exploration of sentiment analysis in low-resource languages, such as Marathi, has been limited due to the availability of suitable datasets. In this work, we present L3Cube-Mah…
Enhancing Low Resource NER Using Assisting Language And Transfer Learning
Maithili Sabane, Aparna Ranade, Onkar Litake +3
Named Entity Recognition (NER) is a fundamental task in NLP that is used to locate the key information in text and is primarily applied in conversational and search systems. In com…
Leveraging Language Identification to Enhance Code-Mixed Text Classification
Gauri Takawane, Abhishek Phaltankar, Varad Patwardhan +3
The usage of more than one language in the same text is referred to as Code Mixed. It is evident that there is a growing degree of adaption of the use of code-mixed data, especiall…
Comparative Study of Pre-Trained BERT Models for Code-Mixed Hindi-English Data
Aryan Patil, Varad Patwardhan, Abhishek Phaltankar +2
The term "Code Mixed" refers to the use of more than one language in the same text. This phenomenon is predominantly observed on social media platforms, with an increasing amount o…
L3Cube-IndicSBERT: A simple approach for learning cross-lingual sentence representations using multilingual BERT
Samruddhi Deode, Janhavi Gadre, Aditi Kajale +2
The multilingual Sentence-BERT (SBERT) models map different languages to common representation space and are useful for cross-language similarity and mining tasks. We propose a sim…