Erik Cambria

Erik Cambria

Nanyang Technological University

H-index: 110

Asia-Singapore

About Erik Cambria

Erik Cambria, With an exceptional h-index of 110 and a recent h-index of 96 (since 2020), a distinguished researcher at Nanyang Technological University, specializes in the field of affective computing, sentiment analysis, multimodal interaction, commonsense reasoning, sentic computing.

His recent articles reflect a diverse array of research interests and contributions to the field:

MICE: A Crosslinguistic Emotion Corpus in Malay, Indonesian, Chinese and English

A Comprehensive Review on Financial Explainable AI

A Wide Evaluation of ChatGPT on Affective Computing Tasks

Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation from Deductive, Inductive and Abductive Views

Granular Syntax Processing with Multi-task and Curriculum Learning

Fusion and Discrimination: A Multimodal Graph Contrastive Learning Framework for Multimodal Sarcasm Detection

Explainable AI for Stress and Depression Detection in the Cyberspace and Beyond

SemEval 2024--Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)

Erik Cambria Information

University

Position

Associate Professor

Citations(all)

50383

Citations(since 2020)

40260

Cited By

22703

hIndex(all)

110

hIndex(since 2020)

96

i10Index(all)

310

i10Index(since 2020)

286

Email

University Profile Page

Nanyang Technological University

Google Scholar

View Google Scholar Profile

Erik Cambria Skills & Research Interests

affective computing

sentiment analysis

multimodal interaction

commonsense reasoning

sentic computing

Top articles of Erik Cambria

Title

Journal

Author(s)

Publication Date

MICE: A Crosslinguistic Emotion Corpus in Malay, Indonesian, Chinese and English

arXiv preprint arXiv:2106.04831

Bee Chin Ng

Yosephine Susanto

Erik Cambria

2021/6/9

A Comprehensive Review on Financial Explainable AI

Wei Jie Yeo

Wihan van der Heever

Rui Mao

Erik Cambria

Ranjan Satapathy

...

2023/9/21

A Wide Evaluation of ChatGPT on Affective Computing Tasks

arXiv preprint arXiv:2308.13911

Mostafa M Amin

Rui Mao

Erik Cambria

Björn W Schuller

2023/8/26

Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation from Deductive, Inductive and Abductive Views

arXiv preprint arXiv:2306.09841

Fangzhi Xu

Qika Lin

Jiawei Han

Tianzhe Zhao

Jun Liu

...

2024

Granular Syntax Processing with Multi-task and Curriculum Learning

Cognitive Computation

Xulang Zhang

Rui Mao

Erik Cambria

2024

Fusion and Discrimination: A Multimodal Graph Contrastive Learning Framework for Multimodal Sarcasm Detection

IEEE Transactions on Affective Computing

Bin Liang

Lin Gui

Yulan He

Erik Cambria

Ruifeng Xu

2024

Explainable AI for Stress and Depression Detection in the Cyberspace and Beyond

Erik Cambria

Balázs Gulyás

Joyce S Pang

Nigel V Marsh

Mythily Subramaniam

2024

SemEval 2024--Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)

arXiv preprint arXiv:2402.18944

Shivani Kumar

Md Shad Akhtar

Erik Cambria

Tanmoy Chakraborty

2024/2/29

Text-based Personality Prediction Using XLNet

Ashok Kumar Jayaraman

Gayathri Ananthakrishnan

Tina Esther Trueman

Erik Cambria

2024

A Review of Deep Learning for Video Captioning

Moloud Abdar

Meenakshi Kollati

Swaraja Kuraparthi

Farhad Pourpanah

Daniel McDuff

...

2024

Quantitative Stock Portfolio Optimization by Multi-task Learning Risk and Return

Information Fusion

Yu Ma*

Rui Mao*

Qika Lin

Peng Wu

Erik Cambria

2024

PrimeNet: A Framework for Commonsense Knowledge Representation and Reasoning Based on Conceptual Primitives

Cognitive Computation

Qian Liu

Sooji Han

Erik Cambria

Yang Li

Kenneth Kwok

2024

Financial Sentiment Analysis: Techniques and Applications

ACM Computing Surveys

Kelvin Du

Frank Xing

Rui Mao

Erik Cambria

2024

Predicting Word Vectors for Microtext

Expert Systems

Iti Chaturvedi

Ranjan Satapathy

Curtis Lynch

Erik Cambria

2024

How Interpretable are Reasoning Explanations from Prompting Large Language Models?

Wei Jie Yeo

Ranjan Satapathy

Goh Siow Mong

Erik Cambria

2024/2/19

Neurosymbolic AI for Mining Public Opinions about Wildfires

Cognitive Computation

Cuc Duong

Vethavikashini Chithrra Raghuram

Amos Lee

Rui Mao

Gianmarco Mengaldo

...

2023/9

Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health

arXiv preprint arXiv:2304.10447

Shaoxiong Ji

Tianlin Zhang

Kailai Yang

Sophia Ananiadou

Erik Cambria

...

2023/4/20

Emotion-and-Knowledge Grounded Response Generation in an Open-domain Dialogue Setting

Knowledge-Based Systems

Deeksha Varshney

Asif Ekbal

Erik Cambria

2024

GPTEval: A Survey on Assessments of ChatGPT and GPT-4

Rui Mao

Guanyi Chen

Xulang Zhang

Frank Guerin

Erik Cambria

2024/6

Self-supervised Utterance Order Prediction for Emotion Recognition in Conversations

Neurocomputing

Dazhi Jiang

Hao Liu

Geng Tu

Runguo Wei

Erik Cambria

2024

See List of Professors in Erik Cambria University(Nanyang Technological University)

Co-Authors

H-index: 109
Björn Schuller

Björn Schuller

Imperial College London

H-index: 89
Louis-Philippe Morency

Louis-Philippe Morency

Carnegie Mellon University

H-index: 75
Guang-Bin Huang

Guang-Bin Huang

Nanyang Technological University

H-index: 55
Shirui Pan

Shirui Pan

Monash University

H-index: 53
Roger Zimmermann

Roger Zimmermann

National University of Singapore

H-index: 38
Luca Oneto

Luca Oneto

Università degli Studi di Genova

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