1 citations · 1 across the 4 of their papers we have counts for
4 papers
FewshotQA: A simple framework for few-shot learning of question answering tasks using pre-trained text-to-text models
Rakesh Chada, Pradeep Natarajan
The task of learning from only a few examples (called a few-shot setting) is of key importance and relevance to a real-world setting. For question answering (QA), the current state…
Error Detection in Large-Scale Natural Language Understanding Systems Using Transformer Models
Rakesh Chada, Pradeep Natarajan, Darshan Fofadiya +1
Large-scale conversational assistants like Alexa, Siri, Cortana and Google Assistant process every utterance using multiple models for domain, intent and named entity recognition.…
Simultaneous paraphrasing and translation by fine-tuning Transformer models
Rakesh Chada
This paper describes the third place submission to the shared task on simultaneous translation and paraphrasing for language education at the 4th workshop on Neural Generation and…
Gendered Pronoun Resolution using BERT and an extractive question answering formulation
Rakesh Chada
The resolution of ambiguous pronouns is a longstanding challenge in Natural Language Understanding. Recent studies have suggested gender bias among state-of-the-art coreference res…