Meng, Fandong

Is chatGPT a good nlg evaluator? A preliminary study

Wang, J., Liang, Y., Meng, F., Sun, Z., Shi, H., Li, Z., Xu, J., Qu, J., & Zhou, J. (2023) · Proceedings of the 4th New Frontiers in Summarization Workshop

Natural Language Processing TechniquesTopic Modeling

Cited by 235

An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-Tuning

Luo, Y., Yang, Z., Meng, F., Li, Y., Zhou, J., & Zhang, Y. (2025) · IEEE Transactions on Audio, Speech and Language Processing

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 136

An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning

Luo, Y., Yang, Z., Meng, F., Li, Y., Zhou, J., & Zhang, Y. (2023) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 135

Unsupervised Paraphrasing by Simulated Annealing

Liu, X., Mou, L., Meng, F., Zhou, H., Zhou, J., & Song, S. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Natural Language Processing TechniquesTopic Modeling

Cited by 75

Infusing Multi-Source Knowledge with Heterogeneous Graph Neural Network for Emotional Conversation Generation

Liang, Y., Meng, F., Zhang, Y., Chen, Y., Xu, J., & Zhou, J. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence

Speech and dialogue systemsEmotion and Mood Recognition

Cited by 63

On Prompt-Driven Safeguarding for Large Language Models

Zheng, C., Yin, F., Zhou, H., Meng, F., Zhou, J., Chang, K.-W., Huang, M., & Peng, N. (2024) · arXiv

Adversarial Robustness in Machine LearningHate Speech and Cyberbullying Detection

Cited by 46

Large Language Models Are Not Robust Multiple Choice Selectors

Zheng, C., Zhou, H., Meng, F., Zhou, J., & Huang, M. (2023) · arXiv

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 29

Instruction Position Matters in Sequence Generation with Large Language Models

Liu, Y., Zeng, X., Meng, F., & Zhou, J. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 14

Improving Translation Faithfulness of Large Language Models via Augmenting Instructions

Chen, Y., Liu, Y., Meng, F., Chen, Y., Xu, J., & Zhou, J. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 8

How Effectively Do Code Language Models Understand Poor-Readability Code?

Hu, C., Chai, Y., Zhou, H., Meng, F., Zhou, J., & Gu, X. (2024) · Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering

Software Engineering ResearchTopic Modeling

Cited by 6

Prevent the Language Model from being Overconfident in Neural Machine Translation

Miao, M., Meng, F., Liu, Y., Zhou, X.-H., & Zhou, J. (2021) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 5

On the token distance modeling ability of higher RoPE attention dimension

Hong, X., Jiang, C., Qi, B., Meng, F., Yu, M., Zhou, B., & Zhou, J. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2