Huang, Songfang

E2E-VLP: End-to-End Vision-Language Pre-training Enhanced by Visual Learning

Xu, H., Yan, M., Li, C., Bi, B., Huang, S., Xiao, W., & Huang, F. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 84

Automated conformance testing for JavaScript engines via deep compiler fuzzing

Ye, G., Tang, Z., Tan, S. H., Huang, S., Fang, D., Sun, X., Bian, L., Wang, H., & Wang, Z. (2021) · Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation

Software Testing and Debugging TechniquesLogic, programming, and type systems

Cited by 77

RRHF: Rank Responses to Align Language Models with Human Feedback without tears

Yuan, Z., Yuan, H., Tan, C., Wang, W., Huang, S., & Huang, F. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 41

How well do Large Language Models perform in Arithmetic tasks?

Yuan, Z., Yuan, H., Tan, C., Wang, W., & Huang, S. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 29

Harder Task Needs More Experts: Dynamic Routing in MoE Models

Huang, Q., An, Z., Zhuang, N., Tao, M., Zhang, C., Jin, Y., Xu, K., Xu, K., Chen, L., Huang, S., et al. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 23