Gao, Hongcheng

Spider2-V: How Far Are Multimodal Agents From Automating Data Science and Engineering Workflows?

Cao, R., Lei, F., Wu, H., Chen, J., Fu, Y., Gao, H., Xiong, X., Zhang, H., Mao, Y., Hu, W., et al. (2024) · Advances in Neural Information Processing Systems 37

Web Data Mining and AnalysisScientific Computing and Data Management

Cited by 15

Kimi k1.5: Scaling Reinforcement Learning with LLMs

Kimi Team, Du, A., Gao, B., Xing, B., Jiang, C., Chen, C., Li, C., Xiao, C., Du, C., Liao, C., et al. (2025) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 12

Revisiting Out-of-distribution Robustness in NLP: Benchmark, Analysis, and LLMs Evaluations

Yuan, L., Chen, Y., Cui, G., Gao, H., Zou, F., Cheng, X., Ji, H., Liu, Z., & Sun, M. (2023) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 8

Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows

Lei, F., Chen, J., Ye, Y., Cao, R., Shin, D., Su, H., Suo, Z., Gao, H., Hu, W., Yin, P., et al. (2024) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 7

Position: Reasoning After Perception Means Reasoning Without Vision

Gao, H., Huang, Z., Tang, J., Xu, L., Li, X., Li, H., Liu, Y., Lin, M., Yang, X., Hu, T., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsVisual Attention and Saliency Detection

Cited by 0