| The Biases of Pre-trained Language Models: An Empirical Study on Prompt-based Sentiment Analysis and Emotion Detection R Mao, Q Liu, K He, W Li, E Cambria IEEE Transactions on Affective Computing 14, 1743-1753 (2023 Best Paper Award), 2023 | 201 | 2023 |
| Word Embedding and WordNet based Metaphor Identification and Interpretation R Mao, C Lin, F Guerin Proceedings of ACL 1, 1222–1231, 2018 | 165 | 2018 |
| A Survey of Large Language Models for Healthcare: From Data, Technology, and Applications to Accountability and Ethics K He, R Mao, Q Lin, Y Ruan, X Lan, M Feng, E Cambria Information Fusion 118, 102963, 2025 | 139 | 2025 |
| End-to-end Sequential Metaphor Identification Inspired by Linguistic Theories R Mao, C Lin, F Guerin Proceedings of ACL, 3888–3898, 2019 | 130 | 2019 |
| Bridging Towers of Multi-task Learning with a Gating Mechanism for Aspect-based Sentiment Analysis and Sequential Metaphor Identification R Mao, X Li Proceedings of AAAI 35 (15), 13534-13542, 2021 | 105 | 2021 |
| Multi-source Aggregated Classification for Stock Price Movement Prediction Y Ma, R Mao, Q Lin, P Wu, E Cambria Information Fusion 91, 515-528, 2023 | 99 | 2023 |
| GPTEval: A Survey on Assessments of ChatGPT and GPT-4 R Mao, G Chen, X Zhang, F Guerin, E Cambria Proceedings of LREC-COLING, 7844–7866, 2024 | 98 | 2024 |
| MetaPro: A Computational Metaphor Processing Model for Text Pre-processing R Mao, X Li, M Ge, E Cambria Information Fusion 86, 30-43, 2022 | 85 | 2022 |
| Meta-based Self-training and Re-weighting for Aspect-based Sentiment Analysis K He, R Mao, T Gong, C Li, E Cambria IEEE Transactions on Affective Computing 14, 1731-1742, 2023 | 82 | 2023 |
| Explainable Metaphor Identification Inspired by Conceptual Metaphor Theory M Ge*, R Mao*, E Cambria Proceedings of AAAI 36 (10), 10681-10689, 2022 | 79 | 2022 |
| Seven Pillars for the Future of Artificial Intelligence E Cambria, R Mao, M Chen, Z Wang, SB Ho IEEE Intelligent Systems 38 (6), 62-69, 2023 | 77 | 2023 |
| COPNER: Contrastive Learning with Prompt Guiding for Few-shot Named Entity Recognition Y Huang, K He, Y Wang, X Zhang, T Gong, R Mao, C Li Proceedings of COLING, 2515-2527, 2022 | 74 | 2022 |
| Hierarchical Attention Network for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings S Han*, R Mao*, E Cambria Proceedings of COLING, 94–104, 2022 | 72 | 2022 |
| KnowleNet: Knowledge Fusion Network for Multimodal Sarcasm Detection T Yue, R Mao, H Wang, Z Hu, E Cambria Information Fusion 100, 101921, 2023 | 70 | 2023 |
| SKIER: A Symbolic Knowledge Integrated Model for Conversational Emotion Recognition W Li, L Zhu, R Mao, E Cambria Proceedings of AAAI 37 (11), 13121-13129, 2023 | 67 | 2023 |
| Virtual Prompt Pre-training for Prototype-based Few-shot Relation Extraction K He, Y Huang, R Mao, T Gong, C Li, E Cambria Expert Systems with Applications 213, 118927, 2023 | 60 | 2023 |
| Fusing Topology Contexts and Logical Rules in Language Models for Knowledge Graph Completion Q Lin, R Mao, J Liu, F Xu, E Cambria Information Fusion 90, 253-264, 2023 | 57 | 2023 |
| SenticNet 8: Fusing emotion AI and commonsense AI for interpretable, trustworthy, and explainable affective computing E Cambria, X Zhang, R Mao, M Chen, K Kwok Proceedings of HCII, 197–216, 2024 | 47 | 2024 |
| MetaPro Online: A Computational Metaphor Processing Online System R Mao, X Li, K He, M Ge, E Cambria Proceedings of ACL: System Demonstrations, 127-135, 2023 | 41 | 2023 |
| TECHS: Temporal Logical Graph Networks for Explainable Extrapolation Reasoning Q Lin, J Liu, R Mao, F Xu, E Cambria Proceedings of ACL, 1281–1293, 2023 | 39 | 2023 |
Erik CambriaProfessor of Artificial Intelligence, CCDS, NTU Singapore確認したメール アドレス: ntu.edu.sg