1 citations · 4 across the 5 of their papers we have counts for
5 papers
Multilingual Bias Detection and Mitigation for Indian Languages
Ankita Maity, Anubhav Sharma, Rudra Dhar +3
Lack of diverse perspectives causes neutrality bias in Wikipedia content leading to millions of worldwide readers getting exposed by potentially inaccurate information. Hence, neut…
Massively Multilingual Language Models for Cross Lingual Fact Extraction from Low Resource Indian Languages
Bhavyajeet Singh, Pavan Kandru, Anubhav Sharma +1
Massive knowledge graphs like Wikidata attempt to capture world knowledge about multiple entities. Recent approaches concentrate on automatically enriching these KGs from text. How…
XF2T: Cross-lingual Fact-to-Text Generation for Low-Resource Languages
Shivprasad Sagare, Tushar Abhishek, Bhavyajeet Singh +3
Multiple business scenarios require an automated generation of descriptive human-readable text from structured input data. Hence, fact-to-text generation systems have been develope…
Adaptation of domain-specific transformer models with text oversampling for sentiment analysis of social media posts on Covid-19 vaccines
Anmol Bansal, Arjun Choudhry, Anubhav Sharma +1
Covid-19 has spread across the world and several vaccines have been developed to counter its surge. To identify the correct sentiments associated with the vaccines from social medi…
XAlign: Cross-lingual Fact-to-Text Alignment and Generation for Low-Resource Languages
Tushar Abhishek, Shivprasad Sagare, Bhavyajeet Singh +3
Multiple critical scenarios (like Wikipedia text generation given English Infoboxes) need automated generation of descriptive text in low resource (LR) languages from English fact…