Devamanyu Hazarika
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Recent trends in deep learning based natural language processing
T Young, D Hazarika, S Poria, E Cambria
IEEE Computational Intelligence Magazine 13, 3, 2017
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
A deeper look into sarcastic tweets using deep convolutional neural networks
S Poria, E Cambria, D Hazarika, P Vij
Proceedings of COLING 2016, the 26th International Conference on …, 2016
SenticNet 5: Discovering conceptual primitives for sentiment analysis by means of context embeddings
E Cambria, S Poria, D Hazarika, K Kwok
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Conversational memory network for emotion recognition in dyadic dialogue videos
D Hazarika, S Poria, A Zadeh, E Cambria, LP Morency, R Zimmermann
Proceedings of the conference. Association for Computational Linguistics …, 2018
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
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
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, 6818-6825, 2019
Cascade: Contextual sarcasm detection in online discussion forums
D Hazarika, S Poria, S Gorantla, E Cambria, R Zimmermann, R Mihalcea
arXiv preprint arXiv:1805.06413, 2018
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
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
Icon: Interactive conversational memory network for multimodal emotion detection
D Hazarika, S Poria, R Mihalcea, E Cambria, R Zimmermann
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
Modeling inter-aspect dependencies for aspect-based sentiment analysis
D Hazarika, S Poria, P Vij, G Krishnamurthy, E Cambria, R Zimmermann
Proceedings of the 2018 Conference of the North American Chapter of the …, 2018
Benchmarking multimodal sentiment analysis
E Cambria, D Hazarika, S Poria, A Hussain, RBV Subramanyam
International Conference on Computational Linguistics and Intelligent Text …, 2017
Self-attentive feature-level fusion for multimodal emotion detection
D Hazarika, S Gorantla, S Poria, R Zimmermann
2018 IEEE Conference on Multimedia Information Processing and Retrieval …, 2018
Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)
S Castro, D Hazarika, V Pérez-Rosas, R Zimmermann, R Mihalcea, ...
arXiv preprint arXiv:1906.01815, 2019
Texture and structure incorporated scatternet hybrid deep learning network (ts-shdl) for brain matter segmentation
A Singh, D Hazarika, A Bhattacharya
Proceedings of the IEEE International Conference on Computer Vision …, 2017
Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Research
S Poria, D Hazarika, N Majumder, R Mihalcea
arXiv preprint arXiv:2005.00357, 2020
MISA: Modality-Invariant and-Specific Representations for Multimodal Sentiment Analysis
D Hazarika, R Zimmermann, S Poria
arXiv preprint arXiv:2005.03545, 2020
Aspect-Sentiment Embeddings for Company Profiling and Employee Opinion Mining
R Bajpai, D Hazarika, K Singh, S Gorantla, E Cambria, R Zimmerman
arXiv preprint arXiv:1902.08342, 2019
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