Published in NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and Applications, 2022
Recommended citation: Sivaprasad Sarath*, Akshay Goindani*, Mario Fritz, and Vineet Gandhi. "Class-wise Domain Generalization: A Novel Framework for Evaluating Distributional Shift." In NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and Applications. https://openreview.net/pdf?id=pkdNspyfcy
Preprint, 2022
Recommended citation: Kodali, P., Sachan, T., Goindani, A., Goel, A., Ahuja, N., Shrivastava, M. and Kumaraguru, P., 2022. PreCogIIITH at HinglishEval:Leveraging Code-Mixing Metrics & Language Model Embeddings To Estimate Code-Mix Quality. arXiv preprint arXiv:2206.07988. https://arxiv.org/pdf/2206.07988.pdf
Preprint, 2021
Recommended citation: Sivaprasad, Sarath*, Akshay Goindani*, Vaibhav Garg, and Vineet Gandhi. "Reappraising Domain Generalization in Neural Networks." arXiv preprint arXiv:2110.07981 (2021). https://arxiv.org/pdf/2110.07981.pdf
Published in International Conference on Recent Advances in Natural Language Processing (RANLP 2021), 2021
Recommended citation: Akshay Goindani, Manish Shrivastava. (2021). "A Dynamic Head Importance Computation Mechanism for Neural Machine Translation" International Conference on Recent Advances in Natural Language Processing (RANLP 2021). 1(1). https://aclanthology.org/2021.ranlp-1.52.pdf
* Authors contributed equally to the work.