8 citations · 14 across the 6 of their papers we have counts for
6 papers
SenTest: Evaluating Robustness of Sentence Encoders
Tanmay Chavan, Shantanu Patankar, Aditya Kane +3
Contrastive learning has proven to be an effective method for pre-training models using weakly labeled data in the vision domain. Sentence transformers are the NLP counterparts to…
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…
A Twitter BERT Approach for Offensive Language Detection in Marathi
Tanmay Chavan, Shantanu Patankar, Aditya Kane +2
Automated offensive language detection is essential in combating the spread of hate speech, particularly in social media. This paper describes our work on Offensive Language Identi…
Spread Love Not Hate: Undermining the Importance of Hateful Pre-training for Hate Speech Detection
Omkar Gokhale, Aditya Kane, Shantanu Patankar +2
Pre-training large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. Although this method has proven to be effectiv…
Optimize_Prime@DravidianLangTech-ACL2022: Abusive Comment Detection in Tamil
Shantanu Patankar, Omkar Gokhale, Onkar Litake +2
This paper tries to address the problem of abusive comment detection in low-resource indic languages. Abusive comments are statements that are offensive to a person or a group of p…
Optimize_Prime@DravidianLangTech-ACL2022: Emotion Analysis in Tamil
Omkar Gokhale, Shantanu Patankar, Onkar Litake +2
This paper aims to perform an emotion analysis of social media comments in Tamil. Emotion analysis is the process of identifying the emotional context of the text. In this paper, w…