Unsupervised Out-of-distribution Detection Using Few In-distribution Samples

Published in ICASSP, 2023

A state-of-the-art baseline for few shot out-of-distribution detection in NLP.

Recommended citation: C. Gautam, A. Kane, S. Ramasamy and S. Sundaram, "Unsupervised Out-of-Distribution Detection Using Few in-Distribution Samples," ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5, doi: 10.1109/ICASSP49357.2023.10096482.

Published in , 1900

Continual VQA for Disaster Response Systems

Published in NeurIPS 2022 Tackling Climate Change with Machine Learning workshop', 2022

We study the VQA problem for the Floodnet dataset in continual and zero shot setting.

Recommended citation: Kane, A., Manushree, V. and Khose, S., 2022. Continual VQA for Disaster Response Systems. arXiv preprint arXiv:2209.10320.

Transformer based ensemble for emotion detection

Published in ACL WASSA Workshop, 2022

Emotion detection using innovative data sampling techniques and ensemble of transformers.

Recommended citation: Aditya Kane, Shantanu Patankar, Sahil Khose, and Neeraja Kirtane. 2022. Transformer based ensemble for emotion detection. In Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, pages 250–254, Dublin, Ireland. Association for Computational Linguistics.