| Meld: A multimodal multi-party dataset for emotion recognition in conversations S Poria, D Hazarika, N Majumder, G Naik, E Cambria, R Mihalcea arXiv preprint arXiv:1810.02508, 2018 | 1228 | 2018 |
| Context-dependent sentiment analysis in user-generated videos S Poria, E Cambria, D Hazarika, N Majumder, A Zadeh, LP Morency Proceedings of the 55th annual meeting of the association for computational …, 2017 | 916 | 2017 |
| Dialoguernn: An attentive rnn for emotion detection in conversations N Majumder, S Poria, D Hazarika, R Mihalcea, A Gelbukh, E Cambria Proceedings of the AAAI conference on artificial intelligence 33 (01), 6818-6825, 2019 | 816 | 2019 |
| Memory fusion network for multi-view sequential learning A Zadeh, PP Liang, N Mazumder, S Poria, E Cambria, LP Morency Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 794 | 2018 |
| Deep learning-based document modeling for personality detection from text N Majumder, S Poria, A Gelbukh, E Cambria IEEE intelligent systems 32 (2), 74-79, 2017 | 675 | 2017 |
| Dialoguegcn: A graph convolutional neural network for emotion recognition in conversation D Ghosal, N Majumder, S Poria, N Chhaya, A Gelbukh arXiv preprint arXiv:1908.11540, 2019 | 644 | 2019 |
| Emotion recognition in conversation: Research challenges, datasets, and recent advances S Poria, N Majumder, R Mihalcea, E Hovy IEEE access 7, 100943-100953, 2019 | 453 | 2019 |
| Recent trends in deep learning based personality detection Y Mehta, N Majumder, A Gelbukh, E Cambria Artificial Intelligence Review 53 (4), 2313-2339, 2020 | 376 | 2020 |
| Multimodal sentiment analysis using hierarchical fusion with context modeling N Majumder, D Hazarika, A Gelbukh, E Cambria, S Poria Knowledge-based systems 161, 124-133, 2018 | 373 | 2018 |
| Cosmic: Commonsense knowledge for emotion identification in conversations D Ghosal, N Majumder, A Gelbukh, R Mihalcea, S Poria arXiv preprint arXiv:2010.02795, 2020 | 343 | 2020 |
| Beneath the tip of the iceberg: Current challenges and new directions in sentiment analysis research S Poria, D Hazarika, N Majumder, R Mihalcea IEEE transactions on affective computing 14 (1), 108-132, 2020 | 273 | 2020 |
| Sentiment and sarcasm classification with multitask learning N Majumder, S Poria, H Peng, N Chhaya, E Cambria, A Gelbukh IEEE Intelligent Systems 34 (3), 38-43, 2019 | 252 | 2019 |
| Multi-level multiple attentions for contextual multimodal sentiment analysis S Poria, E Cambria, D Hazarika, N Mazumder, A Zadeh, LP Morency 2017 IEEE International Conference on Data Mining (ICDM), 1033-1038, 2017 | 223 | 2017 |
| MIME: MIMicking emotions for empathetic response generation N Majumder, P Hong, S Peng, J Lu, D Ghosal, A Gelbukh, R Mihalcea, ... arXiv preprint arXiv:2010.01454, 2020 | 219 | 2020 |
| Multimodal sentiment analysis: Addressing key issues and setting up the baselines S Poria, N Majumder, D Hazarika, E Cambria, A Gelbukh, A Hussain IEEE Intelligent Systems 33 (6), 17-25, 2018 | 215 | 2018 |
| A review of deep learning techniques for speech processing A Mehrish, N Majumder, R Bharadwaj, R Mihalcea, S Poria Information Fusion 99, 101869, 2023 | 176 | 2023 |
| Text-to-audio generation using instruction-tuned llm and latent diffusion model D Ghosal, N Majumder, A Mehrish, S Poria arXiv preprint arXiv:2304.13731, 2023 | 133 | 2023 |
| A deep learning approach for multimodal deception detection G Krishnamurthy, N Majumder, S Poria, E Cambria International Conference on Computational Linguistics and Intelligent Text …, 2018 | 129 | 2018 |
| Investigating gender bias in bert R Bhardwaj, N Majumder, S Poria Cognitive Computation 13 (4), 1008-1018, 2021 | 127 | 2021 |
| IARM: Inter-aspect relation modeling with memory networks in aspect-based sentiment analysis N Majumder, S Poria, A Gelbukh, MS Akhtar, E Cambria, A Ekbal Proceedings of the 2018 conference on empirical methods in natural language …, 2018 | 115 | 2018 |
Soujanya PoriaAssistant Professor, Singapore University of Technology and DesignE-mail confirmado em sutd.edu.sg