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ORCIDErik Cambria
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- affiliation: Nanyang Technological University, Singapore
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2020 – today
- 2024
[j219]Ashok Kumar Jayaraman, Gayathri Ananthakrishnan, Tina Esther Trueman, Erik Cambria:
Chapter Four - Text-based personality prediction using XLNet. Adv. Comput. 132: 49-65 (2024)- [j218]Cuc Duong, Vethavikashini Chithrra Raghuram, Amos Lee, Rui Mao
, Gianmarco Mengaldo, Erik Cambria:
Neurosymbolic AI for Mining Public Opinions about Wildfires. Cogn. Comput. 16(4): 1531-1553 (2024) - [j217]Kelvin Du, Frank Xing, Rui Mao, Erik Cambria:
Financial Sentiment Analysis: Techniques and Applications. ACM Comput. Surv. 56(9): 220:1-220:42 (2024) - [j216]Iti Chaturvedi, Ranjan Satapathy, Curtis Lynch, Erik Cambria:
Predicting word vectors for microtext. Expert Syst. J. Knowl. Eng. 41(8) (2024) - [j215]Ankita Gandhi, Param Ahir, Kinjal Adhvaryu, Pooja Shah, Ritika Lohiya, Erik Cambria, Soujanya Poria, Amir Hussain:
Hate speech detection: A comprehensive review of recent works. Expert Syst. J. Knowl. Eng. 41(8) (2024) - [j214]Mohammad Anas, Anam Saiyeda, Shahab Saquib Sohail, Erik Cambria, Amir Hussain:
Can Generative AI Models Extract Deeper Sentiments as Compared to Traditional Deep Learning Algorithms? IEEE Intell. Syst. 39(2): 5-10 (2024) - [j213]Przemyslaw Kazienko, Erik Cambria:
Toward Responsible Recommender Systems. IEEE Intell. Syst. 39(3): 5-12 (2024) - [j212]Geng Tu, Taiyu Niu, Ruifeng Xu, Bin Liang, Erik Cambria:
AdaCLF: An Adaptive Curriculum Learning Framework for Emotional Support Conversation. IEEE Intell. Syst. 39(4): 5-11 (2024) - [j211]Dazhi Jiang, Hao Liu, Geng Tu, Runguo Wei, Erik Cambria:
Self-supervised utterance order prediction for emotion recognition in conversations. Neurocomputing 577: 127370 (2024) - [j210]Rui Mao, Kai He, Xulang Zhang, Guanyi Chen, Jinjie Ni, Zonglin Yang, Erik Cambria:
A survey on semantic processing techniques. Inf. Fusion 101: 101988 (2024) - [j209]Yu Ma, Rui Mao, Qika Lin, Peng Wu, Erik Cambria:
Quantitative stock portfolio optimization by multi-task learning risk and return. Inf. Fusion 104: 102165 (2024) - [j208]Chunxiao Fan, Jie Lin, Rui Mao, Erik Cambria:
Fusing pairwise modalities for emotion recognition in conversations. Inf. Fusion 106: 102306 (2024) - [j207]Mengyue Liu, Jun Liu, Yixiang Dong, Rui Mao, Erik Cambria:
Interest-driven community detection on attributed heterogeneous information networks. Inf. Fusion 111: 102525 (2024) - [j206]Deeksha Varshney, Asif Ekbal, Erik Cambria:
Emotion-and-knowledge grounded response generation in an open-domain dialogue setting. Knowl. Based Syst. 284: 111173 (2024) - [j205]Xiaoshi Zhong, Chenyu Jin, Mengyu An, Erik Cambria:
XTime: A general rule-based method for time expression recognition and normalization. Knowl. Based Syst. 297: 111921 (2024) - [j204]Weilun Yu, Chengming Li, Xiping Hu, Wenhua Zhu, Erik Cambria, Dazhi Jiang:
Dialogue emotion model based on local-global context encoder and commonsense knowledge fusion attention. Int. J. Mach. Learn. Cybern. 15(7): 2811-2825 (2024) - [j203]Phuong Le-Hong, Erik Cambria:
Integrating graph embedding and neural models for improving transition-based dependency parsing. Neural Comput. Appl. 36(6): 2999-3016 (2024) - [j202]Qian Liu, Xiubo Geng, Yu Wang, Erik Cambria, Daxin Jiang:
Disentangled Retrieval and Reasoning for Implicit Question Answering. IEEE Trans. Neural Networks Learn. Syst. 35(6): 7804-7815 (2024) - [c204]Xiao Wei, Qi Xu, Hang Yu, Qian Liu, Erik Cambria:
Through the MUD: A Multi-Defendant Charge Prediction Benchmark with Linked Crime Elements. ACL (1) 2024: 2864-2878 - [c203]Xulang Zhang, Rui Mao, Erik Cambria:
SenticVec: Toward Robust and Human-Centric Neurosymbolic Sentiment Analysis. ACL (Findings) 2024: 4851-4863 - [c202]Wei Jie Yeo, Ranjan Satapathy, Erik Cambria:
Plausible Extractive Rationalization through Semi-Supervised Entailment Signal. ACL (Findings) 2024: 5182-5192 - [c201]Rui Mao, Kai He, Claudia Ong, Qian Liu, Erik Cambria:
MetaPro 2.0: Computational Metaphor Processing on the Effectiveness of Anomalous Language Modeling. ACL (Findings) 2024: 9891-9908 - [c200]An Tang, Xiuzhen Zhang, Minh Dinh, Erik Cambria:
Prompted Aspect Key Point Analysis for Quantitative Review Summarization. ACL (1) 2024: 10691-10708 - [c199]Zonglin Yang, Xinya Du, Junxian Li, Jie Zheng, Soujanya Poria, Erik Cambria:
Large Language Models for Automated Open-domain Scientific Hypotheses Discovery. ACL (Findings) 2024: 13545-13565 - [c198]Rui Mao, Guanyi Chen, Xulang Zhang, Frank Guerin, Erik Cambria:
GPTEval: A Survey on Assessments of ChatGPT and GPT-4. LREC/COLING 2024: 7844-7866 - [c197]Tan Yue, Xuzhao Shi, Rui Mao, Zonghai Hu, Erik Cambria:
SarcNet: A Multilingual Multimodal Sarcasm Detection Dataset. LREC/COLING 2024: 14325-14335 - [c196]Zonglin Yang, Li Dong, Xinya Du, Hao Cheng, Erik Cambria, Xiaodong Liu, Jianfeng Gao, Furu Wei:
Language Models as Inductive Reasoners. EACL (1) 2024: 209-225 - [c195]Amirhossein Aminimehr, Pouya Khani, Amirali Molaei, Amirmohammad Kazemeini, Erik Cambria:
TbExplain: A Text-Based Explanation Method for Scene Classification Models With the Statistical Prediction Correction. GUIDE-AI@SIGMOD 2024: 54-60 - [c194]Wei Jie Yeo, Ranjan Satapathy, Rich Siow Mong Goh, Erik Cambria:
How Interpretable are Reasoning Explanations from Prompting Large Language Models? NAACL-HLT (Findings) 2024: 2148-2164 - [c193]Erik Cambria, Balázs Gulyás, Joyce S. Pang, Nigel V. Marsh, Mythily Subramaniam:
Explainable AI for Stress and Depression Detection in the Cyberspace and Beyond. PAKDD (Workshops) 2024: 108-120 - [c192]Shivani Kumar, Md. Shad Akhtar, Erik Cambria, Tanmoy Chakraborty:
SemEval 2024 - Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF). SemEval@NAACL 2024: 1933-1946 - [c191]Fanfan Wang, Heqing Ma, Rui Xia, Jianfei Yu, Erik Cambria:
SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations. SemEval@NAACL 2024: 2039-2050 - [i102]Wei Jie Yeo, Ranjan Satapathy, Erik Cambria:
Plausible Extractive Rationalization through Semi-Supervised Entailment Signal. CoRR abs/2402.08479 (2024) - [i101]Wei Jie Yeo, Ranjan Satapathy, Rick Siow Mong Goh, Erik Cambria:
How Interpretable are Reasoning Explanations from Prompting Large Language Models? CoRR abs/2402.11863 (2024) - [i100]Shivani Kumar, Md. Shad Akhtar, Erik Cambria, Tanmoy Chakraborty:
SemEval 2024 - Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF). CoRR abs/2402.18944 (2024) - [i99]Zheng Lian, Haiyang Sun, Licai Sun, Zhuofan Wen, Siyuan Zhang, Shun Chen, Hao Gu, Jinming Zhao, Ziyang Ma, Xie Chen, Jiangyan Yi, Rui Liu, Kele Xu, Bin Liu, Erik Cambria, Guoying Zhao, Björn W. Schuller, Jianhua Tao:
MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition. CoRR abs/2404.17113 (2024) - [i98]Fanfan Wang, Heqing Ma, Jianfei Yu, Rui Xia, Erik Cambria:
SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations. CoRR abs/2405.13049 (2024) - [i97]Shahin Amiriparian, Lukas Christ, Alexander Kathan, Maurice Gerczuk, Niklas Müller, Steffen Klug, Lukas Stappen, Andreas König, Erik Cambria, Björn W. Schuller, Simone Eulitz:
The MuSe 2024 Multimodal Sentiment Analysis Challenge: Social Perception and Humor Recognition. CoRR abs/2406.07753 (2024) - [i96]Wei Jie Yeo, Teddy Ferdinan, Przemyslaw Kazienko, Ranjan Satapathy, Erik Cambria:
Self-training Large Language Models through Knowledge Detection. CoRR abs/2406.11275 (2024) - [i95]Hao Fei, Han Zhang, Bin Wang, Lizi Liao, Qian Liu, Erik Cambria:
EmpathyEar: An Open-source Avatar Multimodal Empathetic Chatbot. CoRR abs/2406.15177 (2024) - [i94]An Quang Tang, Xiuzhen Zhang, Minh Ngoc Dinh, Erik Cambria:
Prompted Aspect Key Point Analysis for Quantitative Review Summarization. CoRR abs/2407.14049 (2024) - [i93]Erik Cambria, Lorenzo Malandri, Fabio Mercorio, Navid Nobani, Andrea Seveso:
XAI meets LLMs: A Survey of the Relation between Explainable AI and Large Language Models. CoRR abs/2407.15248 (2024) - [i92]Keane Ong, Rui Mao, Ranjan Satapathy, Ricardo Shirota Filho, Erik Cambria, Johan Sulaeman, Gianmarco Mengaldo:
Explainable Natural Language Processing for Corporate Sustainability Analysis. CoRR abs/2407.17487 (2024) - 2023
- [j201]Siddique Latif, Heriberto Cuayáhuitl, Farrukh Pervez, Fahad Shamshad, Hafiz Shehbaz Ali, Erik Cambria:
A survey on deep reinforcement learning for audio-based applications. Artif. Intell. Rev. 56(3): 2193-2240 (2023) - [j200]Jinjie Ni, Tom Young, Vlad Pandelea, Fuzhao Xue, Erik Cambria:
Recent advances in deep learning based dialogue systems: a systematic survey. Artif. Intell. Rev. 56(4): 3055-3155 (2023) - [j199]Xulang Zhang, Rui Mao, Erik Cambria:
A survey on syntactic processing techniques. Artif. Intell. Rev. 56(6): 5645-5728 (2023) - [j198]Jingfeng Cui, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria:
Survey on sentiment analysis: evolution of research methods and topics. Artif. Intell. Rev. 56(8): 8469-8510 (2023) - [j197]Xiaoshi Zhong, Erik Cambria:
Time expression recognition and normalization: a survey. Artif. Intell. Rev. 56(9): 9115-9140 (2023) - [j196]Ruicheng Liu, Rui Mao, Anh Tuan Luu, Erik Cambria:
A brief survey on recent advances in coreference resolution. Artif. Intell. Rev. 56(12): 14439-14481 (2023) - [j195]Mengshi Ge, Rui Mao, Erik Cambria:
A survey on computational metaphor processing techniques: from identification, interpretation, generation to application. Artif. Intell. Rev. 56(S2): 1829-1895 (2023) - [j194]Javier Torregrosa, Sergio D'Antonio-Maceiras, Guillermo Villar-Rodríguez, Amir Hussain, Erik Cambria, David Camacho:
A Mixed Approach for Aggressive Political Discourse Analysis on Twitter. Cogn. Comput. 15(2): 440-465 (2023) - [j193]Zhaoxia Wang, Zhenda Hu, Fang Li, Seng-Beng Ho, Erik Cambria:
Learning-Based Stock Trending Prediction by Incorporating Technical Indicators and Social Media Sentiment. Cogn. Comput. 15(3): 1092-1102 (2023) - [j192]Seham Basabain, Erik Cambria, Khalid Alomar, Amir Hussain:
Enhancing Arabic-text feature extraction utilizing label-semantic augmentation in few/zero-shot learning. Expert Syst. J. Knowl. Eng. 40(8) (2023) - [j191]Kai He, Yucheng Huang, Rui Mao, Tieliang Gong, Chen Li, Erik Cambria:
Virtual prompt pre-training for prototype-based few-shot relation extraction. Expert Syst. Appl. 213(Part): 118927 (2023) - [j190]Mostafa M. Amin, Erik Cambria, Björn W. Schuller:
Will Affective Computing Emerge From Foundation Models and General Artificial Intelligence? A First Evaluation of ChatGPT. IEEE Intell. Syst. 38(2): 15-23 (2023) - [j189]Mostafa M. Amin, Erik Cambria, Björn W. Schuller:
Can ChatGPT's Responses Boost Traditional Natural Language Processing? IEEE Intell. Syst. 38(5): 5-11 (2023) - [j188]Erik Cambria, Rui Mao, Melvin Chen, Zhaoxia Wang, Seng-Beng Ho:
Seven Pillars for the Future of Artificial Intelligence. IEEE Intell. Syst. 38(6): 62-69 (2023) - [j187]Tian-Hui You, Ling Ling Tao, Erik Cambria:
A Hotel Ranking Model Through Online Reviews With Aspect-Based Sentiment Analysis. Int. J. Inf. Technol. Decis. Mak. 22(1): 89-113 (2023) - [j186]Qika Lin, Rui Mao, Jun Liu, Fangzhi Xu, Erik Cambria:
Fusing topology contexts and logical rules in language models for knowledge graph completion. Inf. Fusion 90: 253-264 (2023) - [j185]Jintao Wen, Dazhi Jiang, Geng Tu, Cheng Liu, Erik Cambria:
Dynamic interactive multiview memory network for emotion recognition in conversation. Inf. Fusion 91: 123-133 (2023) - [j184]Mauajama Firdaus, Asif Ekbal, Erik Cambria:
Multitask learning for multilingual intent detection and slot filling in dialogue systems. Inf. Fusion 91: 299-315 (2023) - [j183]Ankita Gandhi, Kinjal Adhvaryu, Soujanya Poria, Erik Cambria, Amir Hussain:
Multimodal sentiment analysis: A systematic review of history, datasets, multimodal fusion methods, applications, challenges and future directions. Inf. Fusion 91: 424-444 (2023) - [j182]Yu Ma, Rui Mao, Qika Lin, Peng Wu, Erik Cambria:
Multi-source aggregated classification for stock price movement prediction. Inf. Fusion 91: 515-528 (2023) - [j181]Tan Yue, Rui Mao, Heng Wang, Zonghai Hu, Erik Cambria:
KnowleNet: Knowledge fusion network for multimodal sarcasm detection. Inf. Fusion 100: 101921 (2023) - [j180]Jialun Wu, Kai He, Rui Mao, Chen Li, Erik Cambria:
MEGACare: Knowledge-guided multi-view hypergraph predictive framework for healthcare. Inf. Fusion 100: 101939 (2023) - [j179]Erik Cambria, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani:
A survey on XAI and natural language explanations. Inf. Process. Manag. 60(1): 103111 (2023) - [j178]Qian Liu, Rui Mao, Xiubo Geng, Erik Cambria:
Semantic matching in machine reading comprehension: An empirical study. Inf. Process. Manag. 60(2): 103145 (2023) - [j177]Mohammad Al-Smadi, Mahmoud M. Hammad, Sa'ad A. Al-Zboon, Saja AL-Tawalbeh, Erik Cambria:
Gated recurrent unit with multilingual universal sentence encoder for Arabic aspect-based sentiment analysis. Knowl. Based Syst. 261: 107540 (2023) - [j176]Xiaoshi Zhong, Xiang Yu, Erik Cambria, Jagath C. Rajapakse:
Marshall-Olkin power-law distributions in length-frequency of entities. Knowl. Based Syst. 279: 110942 (2023) - [j175]Phuong Le-Hong, Erik Cambria:
A semantics-aware approach for multilingual natural language inference. Lang. Resour. Evaluation 57(2): 611-639 (2023) - [j174]Zhaoxia Wang, Zhenda Hu, Seng-Beng Ho, Erik Cambria, Ah-Hwee Tan:
MiMuSA - mimicking human language understanding for fine-grained multi-class sentiment analysis. Neural Comput. Appl. 35(21): 15907-15921 (2023) - [j173]Yang Li, Quan Pan, Zhaowen Feng, Erik Cambria:
Few pixels attacks with generative model. Pattern Recognit. 144: 109849 (2023) - [j172]Frank Xing, Björn W. Schuller, Iti Chaturvedi, Erik Cambria, Amir Hussain:
Guest Editorial Neurosymbolic AI for Sentiment Analysis. IEEE Trans. Affect. Comput. 14(3): 1711-1715 (2023) - [j171]Kai He, Rui Mao, Tieliang Gong, Chen Li, Erik Cambria:
Meta-Based Self-Training and Re-Weighting for Aspect-Based Sentiment Analysis. IEEE Trans. Affect. Comput. 14(3): 1731-1742 (2023) - [j170]Rui Mao, Qian Liu, Kai He, Wei Li, Erik Cambria:
The Biases of Pre-Trained Language Models: An Empirical Study on Prompt-Based Sentiment Analysis and Emotion Detection. IEEE Trans. Affect. Comput. 14(3): 1743-1753 (2023) - [j169]Wei Li, Yang Li, Vlad Pandelea, Mengshi Ge, Luyao Zhu, Erik Cambria:
ECPEC: Emotion-Cause Pair Extraction in Conversations. IEEE Trans. Affect. Comput. 14(3): 1754-1765 (2023) - [j168]Dazhi Jiang, Runguo Wei, Jintao Wen, Geng Tu, Erik Cambria:
AutoML-Emo: Automatic Knowledge Selection Using Congruent Effect for Emotion Identification in Conversations. IEEE Trans. Affect. Comput. 14(3): 1845-1856 (2023) - [j167]Luna Ansari, Shaoxiong Ji, Qian Chen, Erik Cambria:
Ensemble Hybrid Learning Methods for Automated Depression Detection. IEEE Trans. Comput. Soc. Syst. 10(1): 211-219 (2023) - [j166]Wei Sun, Shaoxiong Ji, Erik Cambria, Pekka Marttinen:
Multitask Balanced and Recalibrated Network for Medical Code Prediction. ACM Trans. Intell. Syst. Technol. 14(1): 17:1-17:20 (2023) - [j165]Kelvin Du, Frank Xing, Erik Cambria:
Incorporating Multiple Knowledge Sources for Targeted Aspect-based Financial Sentiment Analysis. ACM Trans. Manag. Inf. Syst. 14(3): 23:1-23:24 (2023) - [c190]Wei Li, Luyao Zhu, Rui Mao, Erik Cambria:
SKIER: A Symbolic Knowledge Integrated Model for Conversational Emotion Recognition. AAAI 2023: 13121-13129 - [c189]Rui Mao, Xiao Li, Kai He, Mengshi Ge, Erik Cambria:
MetaPro Online: A Computational Metaphor Processing Online System. ACL (demo) 2023: 127-135 - [c188]Qika Lin, Jun Liu, Rui Mao, Fangzhi Xu, Erik Cambria:
TECHS: Temporal Logical Graph Networks for Explainable Extrapolation Reasoning. ACL (1) 2023: 1281-1293 - [c187]Ran Zhou, Xin Li, Lidong Bing, Erik Cambria, Chunyan Miao:
Improving Self-training for Cross-lingual Named Entity Recognition with Contrastive and Prototype Learning. ACL (1) 2023: 4018-4031 - [c186]Luyao Zhu, Wei Li, Rui Mao, Vlad Pandelea, Erik Cambria:
PAED: Zero-Shot Persona Attribute Extraction in Dialogues. ACL (1) 2023: 9771-9787 - [c185]Jinjie Ni, Rui Mao, Zonglin Yang, Han Lei, Erik Cambria:
Finding the Pillars of Strength for Multi-Head Attention. ACL (1) 2023: 14526-14540 - [c184]Seng-Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria:
Knowledge Representation for Conceptual, Motivational, and Affective Processes in Natural Language Communication. BICS 2023: 14-30 - [c183]Zonglin Yang, Xinya Du, Erik Cambria, Claire Cardie:
End-to-end Case-Based Reasoning for Commonsense Knowledge Base Completion. EACL 2023: 3491-3504 - [c182]Xulang Zhang, Rui Mao, Kai He, Erik Cambria:
Neuro-Symbolic Sentiment Analysis with Dynamic Word Sense Disambiguation. EMNLP (Findings) 2023: 8772-8783 - [c181]Wei Li, Luyao Zhu, Wei Shao, Zonglin Yang, Erik Cambria:
Task-Aware Self-Supervised Framework for Dialogue Discourse Parsing. EMNLP (Findings) 2023: 14162-14173 - [c180]Joni Salminen, Soon-Gyo Jung, Hind A. Al-Merekhi, Erik Cambria, Bernard J. Jansen:
How Can Natural Language Processing and Generative AI Address Grand Challenges of Quantitative User Personas? HCI (53) 2023: 211-231 - [c179]Jinjie Ni, Yukun Ma, Wen Wang, Qian Chen, Dianwen Ng, Han Lei, Trung Hieu Nguyen, Chong Zhang, Bin Ma, Erik Cambria:
Adaptive Knowledge Distillation Between Text and Speech Pre-Trained Models. ICASSP 2023: 1-5 - [c178]Vlad Pandelea, Edoardo Ragusa, Paolo Gastaldo, Erik Cambria:
Selecting Language Models Features VIA Software-Hardware Co-Design. ICASSP 2023: 1-5 - [c177]Hasan Kemik, Nusret Özates, Meysam Asgari-Chenaghlu, Yang Li, Erik Cambria:
BLM-17m: A Large-Scale Dataset for Black Lives Matter Topic Detection on Twitter. ICDM (Workshops) 2023: 736-743 - [c176]Zheng Leitter, Erik Cambria:
Non-Fungible Tokens: What Makes Them Valuable? ICDM (Workshops) 2023: 750-756 - [c175]Andrea Nanetti, John Pavlopoulos, Erik Cambria:
Sentiment Analysis of Primary Historical Sources. ICDM (Workshops) 2023: 767-772 - [c174]Keane Ong, Wihan van der Heever, Ranjan Satapathy, Erik Cambria, Gianmarco Mengaldo:
FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis. ICDM (Workshops) 2023: 773-782 - [c173]Rui Mao, Kelvin Du, Yu Ma, Luyao Zhu, Erik Cambria:
Discovering the Cognition behind Language: Financial Metaphor Analysis with MetaPro. ICDM 2023: 1211-1216 - [c172]Ruicheng Liu, Guanyi Chen, Rui Mao, Erik Cambria:
A Multi-task Learning Model for Gold-two-mention Co-reference Resolution. IJCNN 2023: 1-8 - [c171]Erik Cambria:
ALLEGET Keynote Remarks: Emerging Topics in Sentiment Analysis. Intelligent Environments (Workshops) 2023: 51-52 - [c170]Zheng Lian, Haiyang Sun, Licai Sun, Kang Chen, Mingyu Xu, Kexin Wang, Ke Xu, Yu He, Ying Li, Jinming Zhao, Ye Liu, Bin Liu, Jiangyan Yi, Meng Wang, Erik Cambria, Guoying Zhao, Björn W. Schuller, Jianhua Tao:
MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning. ACM Multimedia 2023: 9610-9614 - [c169]Zheng Lian, Erik Cambria, Guoying Zhao, Björn W. Schuller, Jianhua Tao:
MRAC'23: 1st International Workshop on Multimodal and Responsible Affective Computing. ACM Multimedia 2023: 9713-9714 - [c168]Shahin Amiriparian, Lukas Christ, Andreas König, Alan Cowen, Eva-Maria Meßner, Erik Cambria, Björn W. Schuller:
MuSe 2023 Challenge: Multimodal Prediction of Mimicked Emotions, Cross-Cultural Humour, and Personalised Recognition of Affects. ACM Multimedia 2023: 9723-9725 - [c167]Lukas Christ, Shahin Amiriparian, Alice Baird, Alexander Kathan, Niklas Müller, Steffen Klug, Chris Gagne, Panagiotis Tzirakis, Lukas Stappen, Eva-Maria Meßner, Andreas König, Alan Cowen, Erik Cambria, Björn W. Schuller:
The MuSe 2023 Multimodal Sentiment Analysis Challenge: Mimicked Emotions, Cross-Cultural Humour, and Personalisation. MuSe@ACM Multimedia 2023: 1-10 - [c166]Kelvin Du, Frank Xing, Rui Mao, Erik Cambria:
FinSenticNet: A Concept-Level Lexicon for Financial Sentiment Analysis. SSCI 2023: 109-114 - [e13]Shahin Amiriparian, Lukas Christ, Andreas König, Alan Cowen, Eva-Maria Meßner, Erik Cambria, Björn W. Schuller:
Proceedings of the 4th on Multimodal Sentiment Analysis Challenge and Workshop: Mimicked Emotions, Humour and Personalisation, MuSe 2023, Ottawa, ON, Canada, 2 November 2023. ACM 2023 [contents] - [i91]Keane Ong, Wihan van der Heever, Ranjan Satapathy, Gianmarco Mengaldo, Erik Cambria:
FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis. CoRR abs/2303.02563 (2023) - [i90]Mostafa M. Amin, Erik Cambria, Björn W. Schuller:
Will Affective Computing Emerge from Foundation Models and General AI? A First Evaluation on ChatGPT. CoRR abs/2303.03186 (2023) - [i89]Jinjie Ni, Yukun Ma, Wen Wang, Qian Chen, Dianwen Ng, Han Lei, Trung Hieu Nguyen, Chong Zhang, Bin Ma, Erik Cambria:
Adaptive Knowledge Distillation between Text and Speech Pre-trained Models. CoRR abs/2303.03600 (2023) - [i88]