Cited by 77Topic ModelingMultimodal Machine Learning ApplicationsNatural Language Processing Techniques

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

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Bai, Yushi, Tu, Shangqing, Zhang, Jiajie, Peng, Hao, Wang, Xiaozhi, Lv, Xin, Cao, Shulin, Xu, Jiazheng +4 more·2025·Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Abstract

Yushi Bai, Shangqing Tu, Jiajie Zhang, Hao Peng, Xiaozhi Wang, Xin Lv, Shulin Cao, Jiazheng Xu, Lei Hou, Yuxiao Dong, Jie Tang, Juanzi Li. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.

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Cited by

Sorted by citations

Authors
Bai, Y., Tu, S., Zhang, J., Peng, H., Wang, X., Lv, X., Cao, S., Xu, J., Hou, L., Dong, Y., Tang, J., & Li, J.
Affiliations
  • Tsinghua University (CN)
  • Zhipu AI (China) (CN)
Venue
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Published
2025
Pages
3639-3664
ISSN
0736-587X (ISSN-L)
OpenAlex
W4412886690
Cited by
29
References
0
Citations by year
2026: 25 · 2025: 4
FWCI
27.65
Type
conference paper
Language
en
Open access
Licence
cc-by
Locations
Proceedings of the conference - Association for Computational Linguistics. Meeting (publishedVersion, cc-by)
Funders
National Natural Science Foundation of China
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
  • Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
Keywords
long-context reasoning, large language models, benchmark dataset

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