no code implementations • LREC 2022 • Dibyanayan Bandyopadhyay, Arkadipta De, Baban Gain, Tanik Saikh, Asif Ekbal
We perform experiments on English-Hindi language pairs in the cross-lingual setting to find out that our novel loss formulation could enhance the performance of the baseline model by up to 2%.
no code implementations • CL (ACL) 2022 • Tirthankar Ghosal, Tanik Saikh, Tameesh Biswas, Asif Ekbal, Pushpak Bhattacharyya
In this work, we build upon our earlier investigations for document-level novelty detection and present a comprehensive account of our efforts toward the problem.
no code implementations • 5 Oct 2021 • Tanik Saikh, Sovan Kumar Sahoo, Asif Ekbal, Pushpak Bhattacharyya
This dataset creates a new avenue of carrying out research on COVID-19 by providing a benchmark dataset and a baseline model.
no code implementations • 24 May 2021 • Baban Gain, Dibyanayan Bandyopadhyay, Arkadipta De, Tanik Saikh, Asif Ekbal
The outcomes of this track would be helpful for the automation of the working process of the Indian Judiciary System.
1 code implementation • 17 Apr 2021 • Baban Gain, Dibyanayan Bandyopadhyay, Tanik Saikh, Asif Ekbal
We make use of different Information Retrieval(IR) and deep learning based approaches to tackle these problems.
1 code implementation • ICON 2019 • Tanik Saikh, Arkadipta De, Asif Ekbal, Pushpak Bhattacharyya
We evaluate our techniques on the two recently released datasets, namely FakeNews AMT and Celebrity for fake news detection.
no code implementations • LREC 2020 • Tanik Saikh, Asif Ekbal, Pushpak Bhattacharyya
We present ScholarlyRead, span-of-word-based scholarly articles{'} Reading Comprehension (RC) dataset with approximately 10K manually checked passage-question-answer instances.
no code implementations • WS 2019 • Dibyanayan Bandyopadhyay, Baban Gain, Tanik Saikh, Asif Ekbal
We submitted five system results in each of the NLI and RQE tasks, and four system results for the QA task.