Zhu, Chenguang
Microsoft (United States)
7 papers on CoChatORCID 0000-0002-3549-0826
Most cited papers
- Verified
G-Eval: NLG Evaluation using Gpt-4 with Better Human Alignment
Liu, Y., Iter, D., Xu, Y., Wang, S., Xu, R., & Zhu, C. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Natural Language Processing TechniquesTopic Modeling
Cited by 948
- Verified
G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment
Liu, Y., Iter, D., Xu, Y., Wang, S., Xu, R., & Zhu, C. (2023) · arXiv
Natural Language Processing TechniquesTopic Modeling
Cited by 948
- Verified
Automatic Prompt Optimization with “Gradient Descent” and Beam Search
Pryzant, R., Iter, D., Li, J., Lee, Y., Zhu, C., & Zeng, M. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Topic ModelingNatural Language Processing Techniques
Cited by 191
- Verified
Automatic Prompt Optimization with "Gradient Descent" and Beam Search
Pryzant, R., Iter, D., Li, J., Lee, Y. T., Zhu, C., & Zeng, M. (2023) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 191
- Verified
Towards a Unified Multi-Dimensional Evaluator for Text Generation
Zhong, M., Liu, Y., Yin, D., Mao, Y., Jiao, Y., Liu, P., Zhu, C., Ji, H., & Han, J. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Topic ModelingNatural Language Processing Techniques
Cited by 117
- Verified
SummN: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents
Zhang, Y., Ni, A., Mao, Z., Wu, C. H., Zhu, C., Deb, B., Awadallah, A., Radev, D., & Zhang, R. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Advanced Text Analysis TechniquesTopic Modeling
Cited by 44
- Verified
Towards a Unified Multi-Dimensional Evaluator for Text Generation
Zhong, M., Liu, Y., Yin, D., Mao, Y., Jiao, Y., Liu, P., Zhu, C., Ji, H., & Han, J. (2022) · arXiv
Topic ModelingNatural Language Processing Techniques
Cited by 7
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