CaptainCook4D: A dataset for understanding errors in procedural activities

no code implementations • 22 Dec 2023 • Rohith Peddi, Shivvrat Arya, Bharath Challa, Likhitha Pallapothula, Akshay Vyas, Jikai Wang, Qifan Zhang, Vasundhara Komaragiri, Eric Ragan, Nicholas Ruozzi, Yu Xiang, Vibhav Gogate

Following step-by-step procedures is an essential component of various activities carried out by individuals in their daily lives.

Procedure Learning

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

no code implementations • ICON 2020 • Vibhav Agarwal, Sourav Ghosh, Kranti Chalamalasetti, Bharath Challa, Sonal Kumari, Harshavardhana, Barath Raj Kandur Raja

To the best of our knowledge, this work presents the first lightweight deep learning approach for smartphone deployment of emphasis selection.

LiteMuL: A Lightweight On-Device Sequence Tagger using Multi-task Learning

no code implementations • 15 Dec 2020 • Sonal Kumari, Vibhav Agarwal, Bharath Challa, Kranti Chalamalasetti, Sourav Ghosh, Harshavardhana, Barath Raj Kandur Raja

The proposed LiteMuL not only outperforms the current state of the art results but also surpasses the results of our proposed on-device task-specific models, with accuracy gains of up to 11% and model-size reduction by 50%-56%.

Multi-Task Learning NER +1