1 code implementation • ACL 2022 • Prem Selvaraj, Gokul NC, Pratyush Kumar, Mitesh Khapra
Third, to address the lack of labelled data, we propose self-supervised pretraining on unlabelled data.
no code implementations • ICLR 2018 • Sanchit Agrawal, Gurneet Singh, Mitesh Khapra
(2) The generator (G) is formulated as a continuous function, and the input noise is derived from a connected set, due to which G's output is a connected set.
no code implementations • TACL 2018 • Anoop Kunchukuttan, Mitesh Khapra, Gurneet Singh, Pushpak Bhattacharyya
We address the task of joint training of transliteration models for multiple language pairs (multilingual transliteration).
2 code implementations • ACL 2017 • Preksha Nema, Mitesh Khapra, Anirban Laha, Balaraman Ravindran
Abstractive summarization aims to generate a shorter version of the document covering all the salient points in a compact and coherent fashion.
Ranked #2 on Query-Based Extractive Summarization on Debatepedia
1 code implementation • 1 Apr 2017 • Amrita Saha, Mitesh Khapra, Karthik Sankaranarayanan
With this dataset, we propose 5 new sub-tasks for multimodal conversations along with their evaluation methodology.
no code implementations • 1 Jul 2016 • Rudra Murthy V, Mitesh Khapra, Pushpak Bhattacharyya
In this paper, we propose a neural network based model which allows sharing the decoder as well as word and character level parameters between two languages thereby allowing a resource fortunate language to aid a resource deprived language.
no code implementations • COLING 2014 • Noam Slonim, Ehud Aharoni, Carlos Alzate, Roy Bar-Haim, Yonatan Bilu, Lena Dankin, Iris Eiron, Daniel Hershcovich, Shay Hummel, Mitesh Khapra, Tamar Lavee, Ran Levy, Paul Matchen, Anatoly Polnarov, Vikas Raykar, Ruty Rinott, Amrita Saha, Naama Zwerdling, David Konopnicki, Dan Gutfreund