Yibo Hu

Affiliations:
  • University of Texas at Dallas, Richardson, TX, USA


According to our database1, Yibo Hu authored at least 11 papers between 2021 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Bibliography

2023
Synthesizing Political Zero-Shot Relation Classification via Codebook Knowledge, NLI, and ChatGPT.
CoRR, 2023

WokeGPT: Improving Counterspeech Generation Against Online Hate Speech by Intelligently Augmenting Datasets Using a Novel Metric.
Proceedings of the International Joint Conference on Neural Networks, 2023

2022
ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

CAPT: Contrastive Pre-Training based Semi-Supervised Open-Set Learning.
Proceedings of the 5th IEEE International Conference on Multimedia Information Processing and Retrieval, 2022

Controllable Fake Document Infilling for Cyber Deception.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Knowledge Mining in Cybersecurity: From Attack to Defense.
Proceedings of the Data and Applications Security and Privacy XXXVI, 2022

Confli-T5: An AutoPrompt Pipeline for Conflict Related Text Augmentation.
Proceedings of the IEEE International Conference on Big Data, 2022

Multi-CoPED: A Multilingual Multi-Task Approach for Coding Political Event Data on Conflict and Mediation Domain.
Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021
Uncertainty-Aware Reliable Text Classification.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

CoMe-KE: A New Transformers Based Approach for Knowledge Extraction in Conflict and Mediation Domain.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Multidimensional Uncertainty-Aware Evidential Neural Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021


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