Tu, Shangqing

LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks

Bai, Y., Tu, S., Zhang, J., Peng, H., Wang, X., Lv, X., Cao, S., Xu, J., Hou, L., Dong, Y., et al. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingMultimodal Machine Learning Applications

Cited by 29

KoLA: Carefully Benchmarking World Knowledge of Large Language Models

Yu, J., Wang, X., Tu, S., Cao, S., Zhang-Li, D., Lv, X., Peng, H., Yao, Z., Zhang, X., Li, H., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 29

GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

5 Team, Zeng, A., Lv, X., Zheng, Q., Hou, Z., Chen, B., Xie, C., Wang, C., Yin, D., Zeng, H., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 6

GLM-5: from Vibe Coding to Agentic Engineering

GLM-5-Team, :, Zeng, A., Lv, X., Hou, Z., Du, Z., Zheng, Q., Chen, B., Yin, D., Ge, C., et al. (2026) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 6

LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks

Bai, Y., Tu, S., Zhang, J., Peng, H., Wang, X., Lv, X., Cao, S., Xu, J., Hou, L., Dong, Y., et al. (2024) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 2