Devamanyu Hazarika

8.9k total citations · 5 hit papers
30 papers, 4.7k citations indexed

About

Devamanyu Hazarika is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology. According to data from OpenAlex, Devamanyu Hazarika has authored 30 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 4 papers in Experimental and Cognitive Psychology. Recurrent topics in Devamanyu Hazarika's work include Topic Modeling (18 papers), Natural Language Processing Techniques (12 papers) and Sentiment Analysis and Opinion Mining (11 papers). Devamanyu Hazarika is often cited by papers focused on Topic Modeling (18 papers), Natural Language Processing Techniques (12 papers) and Sentiment Analysis and Opinion Mining (11 papers). Devamanyu Hazarika collaborates with scholars based in Singapore, United States and India. Devamanyu Hazarika's co-authors include Soujanya Poria, Erik Cambria, Tom Young, Roger Zimmermann, Amir Zadeh, Louis–Philippe Morency, Navonil Majumder, Kenneth Kwok, Rada Mihalcea and Alexander Gelbukh and has published in prestigious journals such as IEEE Access, Knowledge-Based Systems and Information Fusion.

In The Last Decade

Devamanyu Hazarika

29 papers receiving 4.5k citations

Hit Papers

Recent Trends in Deep Learning Based Natural Language Pro... 2017 2026 2020 2023 2018 2017 2020 2018 2018 500 1000 1.5k 2.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Recent Trends in Deep Learning Based Natural Language Processing [Review Article]
    2018 2.0k citations Devamanyu Hazarika, Soujanya Poria et al. profile →
  2. Context-Dependent Sentiment Analysis in User-Generated Videos
    2017 531 citations Soujanya Poria, Erik Cambria et al. profile →
  3. MISA
    2020 490 citations Devamanyu Hazarika, Roger Zimmermann et al. profile →
  4. Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos
    2018 294 citations Devamanyu Hazarika, Soujanya Poria et al. PubMed profile →
  5. ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection
    2018 281 citations Devamanyu Hazarika, Soujanya Poria et al. profile →

Peers

Devamanyu Hazarika
Fuji Ren Japan
Dawei Song China
Stefan Wermter Germany
Tong Zhang China
Sicheng Zhao China
Stefanos Kollias Greece
Ashish Kapoor United States
Mari Ostendorf United States
Asif Ekbal India
Prayag Tiwari China
Fuji Ren Japan
Devamanyu Hazarika
Citations per year, relative to Devamanyu Hazarika Devamanyu Hazarika (= 1×) peers Fuji Ren

Countries citing papers authored by Devamanyu Hazarika

Since Specialization
Citations

This map shows the geographic impact of Devamanyu Hazarika's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Devamanyu Hazarika with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Devamanyu Hazarika more than expected).

Fields of papers citing papers by Devamanyu Hazarika

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Devamanyu Hazarika. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Devamanyu Hazarika. The network helps show where Devamanyu Hazarika may publish in the future.

Co-authorship network of co-authors of Devamanyu Hazarika

This figure shows the co-authorship network connecting the top 25 collaborators of Devamanyu Hazarika. A scholar is included among the top collaborators of Devamanyu Hazarika based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Devamanyu Hazarika. Devamanyu Hazarika is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Xu, Yan, et al.. (2023). KILM: Knowledge Injection into Encoder-Decoder Language Models. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 5013–5035. 8 indexed citations
2.
Zhao, Chao, Spandana Gella, Seokhwan Kim, et al.. (2023). “What do others think?”: Task-Oriented Conversational Modeling with Subjective Knowledge. 309–323. 2 indexed citations
3.
Lin, Yen‐Ting, Alexandros Papangelis, Seokhwan Kim, et al.. (2023). Selective In-Context Data Augmentation for Intent Detection using Pointwise V-Information. 1463–1476. 11 indexed citations
4.
Hazarika, Devamanyu, et al.. (2023). Role of Bias Terms in Dot-Product Attention. 1–5. 3 indexed citations
5.
Majumder, Navonil, Deepanway Ghosal, Devamanyu Hazarika, et al.. (2022). Exemplars-Guided Empathetic Response Generation Controlled by the Elements of Human Communication. IEEE Access. 10. 77176–77190. 14 indexed citations
6.
Hazarika, Devamanyu, et al.. (2022). Analyzing Modality Robustness in Multimodal Sentiment Analysis. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 685–696. 30 indexed citations
7.
Chen, Yifan, et al.. (2022). Inducer-tuning: Connecting Prefix-tuning and Adapter-tuning. 793–808. 3 indexed citations
8.
9.
Hazarika, Devamanyu, et al.. (2021). Domain Divergences: A Survey and Empirical Analysis. National University of Singapore. 13 indexed citations
10.
Waheed, Abdul, et al.. (2021). Analyzing the Domain Robustness of Pretrained Language Models, Layer by Layer. National University of Singapore. 222–244. 2 indexed citations
11.
Hazarika, Devamanyu, et al.. (2021). Multimodal research in vision and language: A review of current and emerging trends. Information Fusion. 77. 149–171. 5 indexed citations
12.
Subramanian, Vivek, et al.. (2020). Methods for Numeracy-Preserving Word Embeddings. 4742–4753. 21 indexed citations
13.
Hazarika, Devamanyu, et al.. (2020). Multimodal Research in Vision and Language: A Review of Current and\n Emerging Trends. arXiv (Cornell University). 1 indexed citations
14.
Hazarika, Devamanyu, et al.. (2018). Modeling Inter-Aspect Dependencies for Aspect-Based Sentiment Analysis. 266–270. 63 indexed citations
15.
Hazarika, Devamanyu, Soujanya Poria, Rada Mihalcea, Erik Cambria, & Roger Zimmermann. (2018). ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection. 2594–2604. 281 indexed citations breakdown →
16.
Hazarika, Devamanyu, Soujanya Poria, Amir Zadeh, et al.. (2018). Conversational Memory Network for Emotion Recognition in Dyadic Dialogue Videos. PubMed. 2018. 2122–2132. 294 indexed citations breakdown →
17.
Majumder, Navonil, Devamanyu Hazarika, Alexander Gelbukh, Erik Cambria, & Soujanya Poria. (2018). Multimodal sentiment analysis using hierarchical fusion with context modeling. Knowledge-Based Systems. 161. 124–133. 264 indexed citations
18.
Poria, Soujanya, Erik Cambria, Devamanyu Hazarika, et al.. (2017). Context-Dependent Sentiment Analysis in User-Generated Videos. 873–883. 531 indexed citations breakdown →
19.
Poria, Soujanya, et al.. (2017). Multi-level Multiple Attentions for Contextual Multimodal Sentiment Analysis. 1033–1038. 134 indexed citations
20.
Poria, Soujanya, Erik Cambria, Devamanyu Hazarika, & Prateek Vij. (2016). A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks. International Conference on Computational Linguistics. 1601–1612. 105 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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