134 citations · 546 across the 43 of their papers we have counts for
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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…
Implementing Deep Learning-Based Approaches for Article Summarization in Indian Languages
Rahul Tangsali, Aabha Pingle, Aditya Vyawahare +2
The research on text summarization for low-resource Indian languages has been limited due to the availability of relevant datasets. This paper presents a summary of various deep-le…
L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking BERT Sentence Representations for Hindi and Marathi
Ananya Joshi, Aditi Kajale, Janhavi Gadre +2
Sentence representation from vanilla BERT models does not work well on sentence similarity tasks. Sentence-BERT models specifically trained on STS or NLI datasets are shown to prov…
L3Cube-HindBERT and DevBERT: Pre-Trained BERT Transformer models for Devanagari based Hindi and Marathi Languages
Raviraj Joshi
The monolingual Hindi BERT models currently available on the model hub do not perform better than the multi-lingual models on downstream tasks. We present L3Cube-HindBERT, a Hindi…
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…
Towards Simple and Efficient Task-Adaptive Pre-training for Text Classification
Arnav Ladkat, Aamir Miyajiwala, Samiksha Jagadale +2
Language models are pre-trained using large corpora of generic data like book corpus, common crawl and Wikipedia, which is essential for the model to understand the linguistic char…
A Review of Challenges in Machine Learning based Automated Hate Speech Detection
Abhishek Velankar, Hrushikesh Patil, Raviraj Joshi
The spread of hate speech on social media space is currently a serious issue. The undemanding access to the enormous amount of information being generated on these platforms has le…
On Comparison of Encoders for Attention based End to End Speech Recognition in Standalone and Rescoring Mode
Raviraj Joshi, Subodh Kumar
The streaming automatic speech recognition (ASR) models are more popular and suitable for voice-based applications. However, non-streaming models provide better performance as they…
A Simple Baseline for Domain Adaptation in End to End ASR Systems Using Synthetic Data
Raviraj Joshi, Anupam Singh
Automatic Speech Recognition(ASR) has been dominated by deep learning-based end-to-end speech recognition models. These approaches require large amounts of labeled data in the form…
L3Cube-MahaNLP: Marathi Natural Language Processing Datasets, Models, and Library
Raviraj Joshi
Despite being the third most popular language in India, the Marathi language lacks useful NLP resources. Moreover, popular NLP libraries do not have support for the Marathi languag…
Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi
Abhishek Velankar, Hrushikesh Patil, Raviraj Joshi
Transformers are the most eminent architectures used for a vast range of Natural Language Processing tasks. These models are pre-trained over a large text corpus and are meant to s…
L3Cube-HingCorpus and HingBERT: A Code Mixed Hindi-English Dataset and BERT Language Models
Ravindra Nayak, Raviraj Joshi
Code-switching occurs when more than one language is mixed in a given sentence or a conversation. This phenomenon is more prominent on social media platforms and its adoption is in…
L3Cube-MahaNER: A Marathi Named Entity Recognition Dataset and BERT models
Parth Patil, Aparna Ranade, Maithili Sabane +2
Named Entity Recognition (NER) is a basic NLP task and finds major applications in conversational and search systems. It helps us identify key entities in a sentence used for the d…
Mono vs Multilingual BERT: A Case Study in Hindi and Marathi Named Entity Recognition
Onkar Litake, Maithili Sabane, Parth Patil +2
Named entity recognition (NER) is the process of recognising and classifying important information (entities) in text. Proper nouns, such as a person's name, an organization's name…
L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT Language Models, and Resources
Raviraj Joshi
We present L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources. We expand the existing Marathi monolingual corpus with 24.8M sentences and 289M…
L3Cube-MahaHate: A Tweet-based Marathi Hate Speech Detection Dataset and BERT models
Abhishek Velankar, Hrushikesh Patil, Amol Gore +2
Social media platforms are used by a large number of people prominently to express their thoughts and opinions. However, these platforms have contributed to a substantial amount of…
On Sensitivity of Deep Learning Based Text Classification Algorithms to Practical Input Perturbations
Aamir Miyajiwala, Arnav Ladkat, Samiksha Jagadale +1
Text classification is a fundamental Natural Language Processing task that has a wide variety of applications, where deep learning approaches have produced state-of-the-art results…
Hierarchical Neural Network Approaches for Long Document Classification
Snehal Khandve, Vedangi Wagh, Apurva Wani +2
Text classification algorithms investigate the intricate relationships between words or phrases and attempt to deduce the document's interpretation. In the last few years, these al…