9 citations · 19 across the 5 of their papers we have counts for
4 papers · 1 filter
LIDSNet: A Lightweight on-device Intent Detection model using Deep Siamese Network
Vibhav Agarwal, Sudeep Deepak Shivnikar, Sourav Ghosh +2
Intent detection is a crucial task in any Natural Language Understanding (NLU) system and forms the foundation of a task-oriented dialogue system. To build high-quality real-world…
FONTNET: On-Device Font Understanding and Prediction Pipeline
Rakshith S, Rishabh Khurana, Vibhav Agarwal +2
Fonts are one of the most basic and core design concepts. Numerous use cases can benefit from an in depth understanding of Fonts such as Text Customization which can change text in…
Addressing catastrophic forgetting for medical domain expansion
Sharut Gupta, Praveer Singh, Ken Chang +13
Model brittleness is a key concern when deploying deep learning models in real-world medical settings. A model that has high performance at one institution may suffer a significant…
LiteMuL: A Lightweight On-Device Sequence Tagger using Multi-task Learning
Sonal Kumari, Vibhav Agarwal, Bharath Challa +4
Named entity detection and Parts-of-speech tagging are the key tasks for many NLP applications. Although the current state of the art methods achieved near perfection for long, for…