activity
20202024
most citedLIDSNet: A Lightweight on-device Intent Detection model using Deep Siamese Network

12 citations · 33 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2024★ 5 cited

TrICy: Trigger-guided Data-to-text Generation with Intent aware Attention-Copy

Vibhav Agarwal, Sourav Ghosh, Harichandana BSS +2

Data-to-text (D2T) generation is a crucial task in many natural language understanding (NLU) applications and forms the foundation of task-oriented dialog systems. In the context o…

cs.CV2022★ 9 cited

PrivPAS: A real time Privacy-Preserving AI System and applied ethics

Harichandana B S S, Vibhav Agarwal, Sourav Ghosh +3

With 3.78 billion social media users worldwide in 2021 (48% of the human population), almost 3 billion images are shared daily. At the same time, a consistent evolution of smartpho…

cs.CL2021★ 12 cited

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…

cs.CV2021

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…

cs.LG2021★ 4 cited

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…

cs.CL2021★ 1 cited

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…

cs.CL2020★ 2 cited

EmpLite: A Lightweight Sequence Labeling Model for Emphasis Selection of Short Texts

Vibhav Agarwal, Sourav Ghosh, Kranti Chalamalasetti +4

Word emphasis in textual content aims at conveying the desired intention by changing the size, color, typeface, style (bold, italic, etc.), and other typographical features. The em…