Erik Cambria

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:

Language Models as Inductive Reasoners

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

MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition

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

How Interpretable are Reasoning Explanations from Prompting Large Language Models?

Plausible Extractive Rationalization through Semi-Supervised Entailment Signal

A Dynamic Dual-Graph Neural Network for Stock Price Movement Prediction

SenticNet 8: Fusing Emotion AI and Commonsense AI for Interpretable, Trustworthy, and Explainable Affective Computing

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

Google Scholar

Erik Cambria Skills & Research Interests

affective computing

sentiment analysis

multimodal interaction

commonsense reasoning

sentic computing

Top articles of Erik Cambria

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

arXiv preprint arXiv:2106.04831

2021/6/9

Bee Chin Ng
Bee Chin Ng

H-Index: 9

Erik Cambria
Erik Cambria

H-Index: 72

MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition

arXiv preprint arXiv:2404.17113

2024/4/26

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

arXiv preprint arXiv:2402.18944

2024/2/29

How Interpretable are Reasoning Explanations from Prompting Large Language Models?

2024/2/19

Erik Cambria
Erik Cambria

H-Index: 72

Plausible Extractive Rationalization through Semi-Supervised Entailment Signal

arXiv preprint arXiv:2402.08479

2024/2/13

Erik Cambria
Erik Cambria

H-Index: 72

A Dynamic Dual-Graph Neural Network for Stock Price Movement Prediction

2024

SenticNet 8: Fusing Emotion AI and Commonsense AI for Interpretable, Trustworthy, and Explainable Affective Computing

2024

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

2024

Erik Cambria
Erik Cambria

H-Index: 72

Predicting Word Vectors for Microtext

Expert Systems

2024

Erik Cambria
Erik Cambria

H-Index: 72

Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms?

IEEE Intelligent Systems

2024

Hate Speech Detection: A Comprehensive Review of Recent Works

Expert Systems

2024

Fusing Pairwise Modalities for Emotion Recognition in Conversations

Information Fusion

2024/3

Jie Lin
Jie Lin

H-Index: 1

Rui Mao
Rui Mao

H-Index: 7

Erik Cambria
Erik Cambria

H-Index: 72

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

IEEE Transactions on Affective Computing

2024

Bin Liang
Bin Liang

H-Index: 33

Erik Cambria
Erik Cambria

H-Index: 72

Financial Sentiment Analysis: Techniques and Applications

ACM Computing Surveys

2024

Self-supervised Utterance Order Prediction for Emotion Recognition in Conversations

Neurocomputing

2024

ArabiziVec: A Set of Arabizi Word Embeddings for Informal Arabic Sentiment Analysis

2024

Erik Cambria
Erik Cambria

H-Index: 72

Yashvardhan Sharma
Yashvardhan Sharma

H-Index: 8

Dialogue Emotion Model based on Local-Global Context Encoder and Commonsense Knowledge Fusion Attention

International Journal of Machine Learning and Cybernetics

2024

Dazhi Jiang
Dazhi Jiang

H-Index: 14

Erik Cambria
Erik Cambria

H-Index: 72

Granular Syntax Processing with Multi-task and Curriculum Learning

Cognitive Computation

2024

Rui Mao
Rui Mao

H-Index: 7

Erik Cambria
Erik Cambria

H-Index: 72

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

Information Fusion

2024

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

Co-Authors

academic-engine