6 citations · 24 across the 15 of their papers we have counts for
5 papers · 1 filter
Sensi-BERT: Towards Sensitivity Driven Fine-Tuning for Parameter-Efficient BERT
Souvik Kundu, Sharath Nittur Sridhar, Maciej Szankin +1
Large pre-trained language models have recently gained significant traction due to their improved performance on various down-stream tasks like text classification and question ans…
Svarah: Evaluating English ASR Systems on Indian Accents
Tahir Javed, Sakshi Joshi, Vignesh Nagarajan +6
India is the second largest English-speaking country in the world with a speaker base of roughly 130 million. Thus, it is imperative that automatic speech recognition (ASR) systems…
Vistaar: Diverse Benchmarks and Training Sets for Indian Language ASR
Kaushal Santosh Bhogale, Sai Sundaresan, Abhigyan Raman +3
Improving ASR systems is necessary to make new LLM-based use-cases accessible to people across the globe. In this paper, we focus on Indian languages, and make the case that divers…
TrimBERT: Tailoring BERT for Trade-offs
Sharath Nittur Sridhar, Anthony Sarah, Sairam Sundaresan
Models based on BERT have been extremely successful in solving a variety of natural language processing (NLP) tasks. Unfortunately, many of these large models require a great deal…
Logic2Text: High-Fidelity Natural Language Generation from Logical Forms
Zhiyu Chen, Wenhu Chen, Hanwen Zha +4
Previous works on Natural Language Generation (NLG) from structured data have primarily focused on surface-level descriptions of record sequences. However, for complex structured d…