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opensource
GSoC 2022 at TensorFlow : Final Report
Contribute to KerasCV and KerasNLP
portfolio
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publications
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. https://aclanthology.org/2022.wassa-1.25/
An Efficient Modern Baseline for FloodNet VQA
Published in ICML NewInML Workshop, 2022
A state-of-the-art baseline for VQA on the FloodNet dataset. Won the Second Best Paper award in NewInML Workshop 2022.
Recommended citation: Kane, Aditya and Sahil Khose. “An Efficient Modern Baseline for FloodNet VQA.” (2022). https://arxiv.org/pdf/2205.15025.pdf
Large Language Models for Multi-label Propaganda Detection
Published in EMNLP Arabic Natural Language Processing Workshop, 2022
Ablation of Arabic models for propoganda detection in Arabic.
Recommended citation: Chavan, Tanmay and kane, Aditya. “Large Language Models for Multi-label Propaganda Detection” (2022). https://arxiv.org/abs/2210.08209
Temporal Word Meaning Disambiguation using TimeLMs
Published in EMNLP 2022 EvoNLP workshop, 2022
We study two methods for word sense disamiguation using temporal components.
Recommended citation: Godbole, M., Dandavate, P. and Kane, A., 2022. Temporal Word Meaning Disambiguation using TimeLMs. arXiv preprint arXiv:2210.08207. https://arxiv.org/abs/2210.08207
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. https://arxiv.org/abs/2209.10320
Efficient Gender Debiasing of Pre-trained Indic Language Models
Published in AAAI 2023 Deployable AI workshop, 2022
A state-of-the-art baseline for VQA on the FloodNet dataset. Won the Second Best Paper award in NewInML Workshop 2022.
Recommended citation: Kirtane, N., Manushree, V. and Kane, A., 2022. Efficient Gender Debiasing of Pre-trained Indic Language Models. arXiv preprint arXiv:2209.03661. https://arxiv.org/abs/2209.03661
A Twitter BERT Approach for Offensive Language Detection in Marathi
Published in FIRE 2022 workshop, 2022
Applying LLMs to offensive language detection in Marathi.
Recommended citation: Chavan, T., Patankar, S., Kane, A., Gokhale, O. and Joshi, R., 2022. A Twitter BERT Approach for Offensive Language Detection in Marathi. arXiv preprint arXiv:2212.10039. https://arxiv.org/abs/2212.10039
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. https://ieeexplore.ieee.org/abstract/document/10096482
Two-stage Pipeline for Multilingual Dialect Detection
Published in EACL VarDial Workshop, 2023
A two-stage end-to-end deep learning based pipeline for multilingual dialect detection.
Recommended citation: Vaidya, A. and Kane, A., 2023. Two-stage Pipeline for Multilingual Dialect Detection. arXiv preprint arXiv:2303.03487. https://arxiv.org/pdf/2303.03487.pdf
talks
Google Summer of Code and Open Source in ML
Published:
Delivered a talk on getting started with open-source in ML and Google Summer of Code.
Open Source in ML
Published:
Delivered a talk on getting started with open-source in ML.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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