Navonil Majumder
Cited by
Cited by
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
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
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
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
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
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
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
Recent trends in deep learning based personality detection
Y Mehta, N Majumder, A Gelbukh, E Cambria
Artificial Intelligence Review 53 (4), 2313-2339, 2020
Emotion recognition in conversation: Research challenges, datasets, and recent advances
S Poria, N Majumder, R Mihalcea, E Hovy
IEEE Access 7, 100943-100953, 2019
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
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
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
Cosmic: Commonsense knowledge for emotion identification in conversations
D Ghosal, N Majumder, A Gelbukh, R Mihalcea, S Poria
arXiv preprint arXiv:2010.02795, 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, 2020
A deep learning approach for multimodal deception detection
G Krishnamurthy, N Majumder, S Poria, E Cambria
arXiv preprint arXiv:1803.00344, 2018
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
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
Investigating gender bias in bert
R Bhardwaj, N Majumder, S Poria
Cognitive Computation 13 (4), 1008-1018, 2021
Kingdom: Knowledge-guided domain adaptation for sentiment analysis
D Ghosal, D Hazarika, A Roy, N Majumder, R Mihalcea, S Poria
arXiv preprint arXiv:2005.00791, 2020
Multimodal research in vision and language: A review of current and emerging trends
S Uppal, S Bhagat, D Hazarika, N Majumder, S Poria, R Zimmermann, ...
Information Fusion 77, 149-171, 2022
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