Hazarika, Devamanyu
8 papers on CoChatORCID 0000-0002-0241-7163
Most cited papers
- Verified
Recent Trends in Deep Learning Based Natural Language Processing [Review Article]
Young, T., Hazarika, D., Poria, S., & Cambria, E. (2018) · IEEE Computational Intelligence Magazine
Topic ModelingNatural Language Processing Techniques
Cited by 2,921
- Verified
MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations
Poria, S., Hazarika, D., Majumder, N., Naik, G., Cambria, E., & Mihalcea, R. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Emotion and Mood RecognitionSentiment Analysis and Opinion Mining
Cited by 1,416
- Verified
MISA: Modality-Invariant and -Specific Representations for Multimodal Sentiment Analysis
Hazarika, D., Zimmermann, R., & Poria, S. (2020) · Proceedings of the 28th ACM International Conference on Multimedia
Sentiment Analysis and Opinion MiningEmotion and Mood Recognition
Cited by 1,073
- Verified
Context-Dependent Sentiment Analysis in User-Generated Videos
Poria, S., Cambria, E., Hazarika, D., Majumder, N., Zadeh, A., & Morency, L.-P. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Sentiment Analysis and Opinion MiningEmotion and Mood Recognition
Cited by 939
- Verified
Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)
Castro, S., Hazarika, D., Pérez-Rosas, V., Zimmermann, R., Mihalcea, R., & Poria, S. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Sentiment Analysis and Opinion MiningHate Speech and Cyberbullying Detection
Cited by 243
- Verified
Analyzing Modality Robustness in Multimodal Sentiment Analysis
Hazarika, D., Li, Y., Cheng, B., Zhao, S., Zimmermann, R., & Poria, S. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Sentiment Analysis and Opinion MiningEmotion and Mood Recognition
Cited by 51
- Verified
Using In-Context Learning to Improve Dialogue Safety
Meade, N., Gella, S., Hazarika, D., Gupta, P., Jin, D., Reddy, S., Liu, Y., & Hakkani-Tur, D. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023
Speech and dialogue systemsHate Speech and Cyberbullying Detection
Cited by 13
- Verified
Do LLMs Recognize Your Preferences? Evaluating Personalized Preference Following in LLMs
Zhao, S., Hong, M., Liu, Y., Hazarika, D., & Lin, K. (2025) · arXiv
Speech and dialogue systemsTopic Modeling
Cited by 3
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