Du, Xinya
The University of Texas at Dallas
9 papers on CoChat
Most cited papers
- Verified
Learning to Ask: Neural Question Generation for Reading Comprehension
Du, X., Shao, J., & Cardie, C. (2017) · Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Topic ModelingNatural Language Processing Techniques
Cited by 696
- Verified
Harvesting Paragraph-level Question-Answer Pairs from Wikipedia
Du, X., & Cardie, C. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Topic ModelingNatural Language Processing Techniques
Cited by 168
- Verified
PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations
Li, R., Patel, T., & Du, X. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 110
- Verified
Identifying Where to Focus in Reading Comprehension for Neural Question Generation
Du, X., & Cardie, C. (2017) · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Topic ModelingNatural Language Processing Techniques
Cited by 100
- Verified
Retrieval-Augmented Generative Question Answering for Event Argument Extraction
Du, X., & Ji, H. (2022) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 37
- Verified
Large Language Models for Automated Open-domain Scientific Hypotheses Discovery
Yang, Z., Du, X., Li, J., Zheng, J., Poria, S., & Cambria, E. (2023) · arXiv
Topic ModelingMultimodal Machine Learning Applications
Cited by 34
- Verified
FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models
Jing, L., Li, R., Chen, Y., & Du, X. (2023) · arXiv
Multimodal Machine Learning ApplicationsTopic Modeling
Cited by 31
- Verified
Leveraging Structured Information for Explainable Multi-hop Question Answering and Reasoning
Li, R., & Du, X. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023
Topic ModelingExplainable Artificial Intelligence (XAI)
Cited by 12
- Verified
DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?
Jing, L., Huang, Z., Wang, X., Yao, W., Yu, W., Ma, K., Zhang, H., Du, X., & Yu, D. (2024) · arXiv
Topic ModelingArtificial Intelligence Applications
Cited by 1
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