
PUBLICATIONS
“My expedition is the sea of stars.”
Journal Papers
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Mao R., Liu Q., He K., Li W., Cambria E. (2023). The Biases of Pre-trained Language Models: An Empirical
Study on Prompt-based Sentiment Analysis and Emotion Detection. IEEE Transactions on Affective Computing. [paper]
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Liu Q., Mao R., Geng X., Cambria E. (2023). Semantic Matching in Machine Reading Comprehension: An
Empirical Study. Information Processing and Management. 60(2):103145. [paper]
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Ma Y., Mao R., Lin Q., Wu P., Cambria E. (2023). Multi-source Aggregated Classification for Stock PriceMovement Prediction. Information Fusion. 91:515-528. [paper]
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Lin Q., Mao R., Liu J., Xu F., Cambria E. (2023). Fusing Topology Contexts and Logical Rules in LanguageModels for Knowledge Graph Completion. Information Fusion. 90:253-264. [paper]
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He K., Huang Y., Mao R., Gong T., Li C., Cambria E. (2023). Virtual Prompt Pre-training for Prototype-basedFew-shot Relation Extraction. Expert Systems with Applications. 213:118927. [paper]
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Zhang X., Mao R., Cambria E. (2023). A Survey on Syntactic Processing Techniques. Artificial Intelligence
Review. 56:5645–5728. [paper]
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Liu R., Mao R., Luu A. T., Cambria E. (2023). A Brief Survey on Advances in Coreference Resolution. Artificial Intelligence Review.
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He K., Mao R., Gong T., Cambria E., Li C. (2022). JCBIE: A Joint Continual Learning Neural Network for Biomedical Information Extraction. BMC Bioinformatics, 23:549. [paper]
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Mao R., Li X., Ge M., Cambria E. (2022). MetaPro: A Computational Metaphor Processing System for Text
Pre-processing. Information Fusion, 86-87:30-43. [paper]
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He K., Mao R., Gong T., Li C., Cambria E. (2022). Meta-based Self-training and Re-weighting for Aspect-based
Sentiment Analysis. IEEE Transactions on Affective Computing. [paper]
Conference Papers
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Mao R., Li X., He K., Ge M., Cambria E. (2023). MetaPro Online: A Computational Metaphor Processing Online System. In Proceedings of ACL. (Demonstration Track)
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Ni J., Mao R., Yang Z., Lei H. Cambria E. (2023). Finding the Pillars of Strength for Multi-Head Attention. In Proceedings of ACL. (full)
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Lin Q., Liu J., Mao R., Xu F., Cambria E. (2023). TECHS: Temporal Logical Graph Networks for Explainable Extrapolation Reasoning. In Proceedings of ACL. (full)
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Zhu L., Li W., Mao R., Pandelea V., Cambria E. (2023). PAED: Zero-Shot Persona Attribute Extraction in Dialogues. In Proceedings of ACL. (full)
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Li W., Zhu L., Mao R., Cambria E. (2023). SKIER: A Symbolic Knowledge Integrated Model for Conversational Emotion Recognition. In Proceedings of AAAI. (full)
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Liu, R., Chen, G., Mao, R., Cambria, E. (2023). A Multi-task Learning Model for Gold-two-mention Co-reference Resolution. Proceedings of IJCNN. (full)
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Ge, M.*, Mao, R.*, Cambira, E. (2022). Explainable Metaphor Identification Inspired by Conceptual Metaphor Theory. In Proceedings of AAAI. (full) [paper]
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Han S.*, Mao R.*, Cambria E. (2022). Hierarchical Attention Network for Explainable Depression Detection on Twitter Aided by Metaphor Concept Mappings. In Proceedings of COLING. (full) [paper]
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Huang Y., He K., Wang Y., Zhang X., Gong T., Mao R., Li C. (2022). COPNER: Contrastive Learning with
Prompt Guiding for Few-shot Named Entity Recognition. In Proceedings of COLING. (full) [paper]
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Duong C., Liu Q., Mao R., Cambria E. (2022). Saving Earth One Tweet at a Time through the Lens of Artificial
Intelligence. In Proceedings of IJCNN. (full) [paper]
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Mao, R., & Li, X. (2021). Bridging Towers of Multi-task Learning with a Gating Mechanism for Aspect-based Sentiment Analysis and Sequential Metaphor Identification. In Proceedings of AAAI. (full) [paper]
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Mao, R., Lin, C. & Guerin, F. (2019). End-to-End Sequential Metaphor Identification Inspired by Linguistic Theories. In Proceedings of ACL. (full) [paper]
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Li R., Li X., Lin C., Collinson M., Mao R. (2019) A Stable Variational Autoencoder for Text Modelling. In
Proceedings of INLG. (shot, best paper runner-up) [paper]
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Mao, R., Lin, C. & Guerin, F. (2018). Word Embedding and WordNet Based Metaphor Identification and Interpretation. In Proceedings of ACL. (full) [paper]
Workshop Papers
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Cambria E., Mao R., Liu Q., Han S. (2022). Sentic Parser: A Graph-Based Approach to Concept Extraction for Sentiment Analysis. In Proceedings of ICDM Workshops. [paper]
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Mao, R., Chen, G., Li, R. & Lin, C. ABDN at SemEval-2018 Task 10: Recognising Discriminative Attributes using Context Embeddings and WordNet. In Proceedings of SemEval-NAACL. [paper]