Resources

By downloading you agree to use the datasets for research purpose only and cite the below paper.

Humair Raj Khan*, Deepak Gupta*, Asif Ekbal Towards Developing a Multilingual and Code-Mixed Visual Question Answering System by Knowledge Distillation Findings of the Association for Computational Linguistics: EMNLP 2021

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Deepak Gupta, Pabitra Lenka, Asif Ekbal, Pushpak Bhattacharyya A Unified Framework for Multilingual and Code-Mixed Visual Question Answering. In Proceedings of the Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing (AACL).

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Gupta, D., Ekbal, A. and Bhattacharyya, P., 2020, November. A Semi-supervised Approach to Generate the Code-Mixed Text using Pre-trained Encoder and Transfer Learning. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings (pp. 2267-2280).

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DEEPAK GUPTA, ASIF EKBAL, and PUSHPAK BHATTACHARYYA, A Deep Neural Network Framework for English Hindi Question Answering, In the ACM Trans. Asian Low-Resour. Lang. Inf. Process., Vol. 19, No. 2, Article 25. Publication date: November 2019.

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Deepak Gupta, Pabitra Lenka, Asif Ekbal, Pushpak Bhattacharyya, Uncovering Code-Mixed Challenges: A Framework for Linguistically Driven Question Generation and Neural Based Question Answering, In the Proceedings of the 22nd Conference on Computational Natural Language Learning.

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Deepak Gupta, Rajkumar Pujari, Asif Ekbal, Pushpak Bhattacharyya, Anutosh Maitra, Tom Jain, Shubhashis Sengupta, Can Taxonomy Help? Improving Semantic Question Matching using Question Taxonomy, In the Proceedings of the 27th International Conference on Computational Linguistics.

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Deepak Gupta, Surabhi Kumari, Asif Ekbal, Pushpak Bhattacharyya, MMQA: A Multi-domain Multi-lingual Question-Answering Framework for English and Hindi, In the Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).