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2020 – today
- 2025
[i14]Kimi Team, Angang Du, Bofei Gao, Bowei Xing, Changjiu Jiang, Cheng Chen, Cheng Li, Chenjun Xiao, Chenzhuang Du, Chonghua Liao, Chuning Tang, Congcong Wang, Dehao Zhang, Enming Yuan, Enzhe Lu, Fengxiang Tang, Flood Sung, Guangda Wei, Guokun Lai, Haiqing Guo, Han Zhu, Hao Ding, Hao Hu, Hao Yang, Hao Zhang, Haotian Yao, Haotian Zhao, Haoyu Lu, Haoze Li, Haozhen Yu, Hongcheng Gao, Huabin Zheng, Huan Yuan, Jia Chen, Jianhang Guo, Jianlin Su, Jianzhou Wang, Jie Zhao, Jin Zhang, Jingyuan Liu, Junjie Yan, Junyan Wu, Lidong Shi, Ling Ye, Longhui Yu, Mengnan Dong, Neo Zhang, Ningchen Ma, Qiwei Pan, Qucheng Gong, Shaowei Liu, Shengling Ma, Shupeng Wei, Sihan Cao, Siying Huang, Tao Jiang, Weihao Gao, Weimin Xiong, Weiran He, Weixiao Huang, Wenhao Wu, Wenyang He, Xianghui Wei, Xianqing Jia, Xingzhe Wu, Xinran Xu, Xinxing Zu, Xinyu Zhou, Xuehai Pan, Y. Charles, Yang Li, Yangyang Hu, Yangyang Liu, Yanru Chen, Yejie Wang, Yibo Liu, Yidao Qin, Yifeng Liu, Ying Yang, Yiping Bao, Yulun Du, Yuxin Wu, Yuzhi Wang, Zaida Zhou, Zhaoji Wang, Zhaowei Li, Zhen Zhu, Zheng Zhang, Zhexu Wang, Zhilin Yang, Zhiqi Huang, Zihao Huang, Ziyao Xu, Zonghan Yang:
Kimi k1.5: Scaling Reinforcement Learning with LLMs. CoRR abs/2501.12599 (2025)- [i13]Enzhe Lu, Zhejun Jiang, Jingyuan Liu, Yulun Du, Tao Jiang, Chao Hong, Shaowei Liu, Weiran He, Enming Yuan, Yuzhi Wang, Zhiqi Huang, Huan Yuan, Suting Xu, Xinran Xu, Guokun Lai, Yanru Chen, Huabin Zheng, Junjie Yan, Jianlin Su, Yuxin Wu, Neo Y. Zhang, Zhilin Yang, Xinyu Zhou, Mingxing Zhang, Jiezhong Qiu:
MoBA: Mixture of Block Attention for Long-Context LLMs. CoRR abs/2502.13189 (2025) - [i12]Jingyuan Liu, Jianlin Su, Xingcheng Yao, Zhejun Jiang, Guokun Lai, Yulun Du, Yidao Qin, Weixin Xu, Enzhe Lu, Junjie Yan, Yanru Chen, Huabin Zheng, Yibo Liu, Shaowei Liu, Bohong Yin, Weiran He, Han Zhu, Yuzhi Wang, Jianzhou Wang, Mengnan Dong, Zheng Zhang, Yongsheng Kang, Hao Zhang, Xinran Xu, Yutao Zhang, Yuxin Wu, Xinyu Zhou, Zhilin Yang:
Muon is Scalable for LLM Training. CoRR abs/2502.16982 (2025) - 2023
- [i11]Ruohong Zhang, Luyu Gao, Chen Zheng, Zhen Fan, Guokun Lai, Zheng Zhang, Fangzhou Ai, Yiming Yang, Hongxia Yang:
A Self-enhancement Approach for Domain-specific Chatbot Training via Knowledge Mining and Digest. CoRR abs/2311.10614 (2023) - 2020
- [c8]Ruohong Zhang, Yu Hao, Donghan Yu, Wei-Cheng Chang, Guokun Lai, Yiming Yang:
Correlation-Aware Change-Point Detection via Graph Neural Networks. ICONIP (3) 2020: 555-567 - [c7]Zihang Dai, Guokun Lai, Yiming Yang, Quoc Le:
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. NeurIPS 2020 - [i10]Ruohong Zhang, Yu Hao, Donghan Yu, Wei-Cheng Chang, Guokun Lai, Yiming Yang:
Explainable Unsupervised Change-point Detection via Graph Neural Networks. CoRR abs/2004.11934 (2020) - [i9]Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le:
Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. CoRR abs/2006.03236 (2020) - [i8]Guokun Lai, Zihang Dai, Yiming Yang:
Unsupervised Parallel Corpus Mining on Web Data. CoRR abs/2009.08595 (2020)
2010 – 2019
- 2019
- [c6]Guokun Lai, Zihang Dai, Yiming Yang, Shinjae Yoo:
Re-examination of the Role of Latent Variables in Sequence Modeling. NeurIPS 2019: 7812-7822 - [i7]Zihang Dai, Guokun Lai, Yiming Yang, Shinjae Yoo:
Re-examination of the Role of Latent Variables in Sequence Modeling. CoRR abs/1902.01388 (2019) - [i6]Guokun Lai, Barlas Oguz, Yiming Yang, Veselin Stoyanov:
Bridging the domain gap in cross-lingual document classification. CoRR abs/1909.07009 (2019) - 2018
- [c5]Qizhe Xie, Guokun Lai, Zihang Dai, Eduard H. Hovy:
Large-scale Cloze Test Dataset Created by Teachers. EMNLP 2018: 2344-2356 - [c4]Guokun Lai, Wei-Cheng Chang, Yiming Yang, Hanxiao Liu:
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks. SIGIR 2018: 95-104 - [i5]Guokun Lai, Bohan Li, Guoqing Zheng, Yiming Yang:
Stochastic WaveNet: A Generative Latent Variable Model for Sequential Data. CoRR abs/1806.06116 (2018) - 2017
- [c3]Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, Eduard H. Hovy:
RACE: Large-scale ReAding Comprehension Dataset From Examinations. EMNLP 2017: 785-794 - [i4]Guokun Lai, Wei-Cheng Chang, Yiming Yang, Hanxiao Liu:
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks. CoRR abs/1703.07015 (2017) - [i3]Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, Eduard H. Hovy:
RACE: Large-scale ReAding Comprehension Dataset From Examinations. CoRR abs/1704.04683 (2017) - [i2]Guokun Lai, Hanxiao Liu, Yiming Yang:
Learning Graph Convolution Filters from Data Manifold. CoRR abs/1710.11577 (2017) - [i1]Qizhe Xie, Guokun Lai, Zihang Dai, Eduard H. Hovy:
Large-scale Cloze Test Dataset Designed by Teachers. CoRR abs/1711.03225 (2017) - 2015
- [c2]Yongfeng Zhang, Min Zhang, Yi Zhang
, Guokun Lai, Yiqun Liu, Honghui Zhang, Shaoping Ma:
Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis. WWW 2015: 1373-1383 - 2014
- [c1]Yongfeng Zhang, Guokun Lai, Min Zhang, Yi Zhang, Yiqun Liu, Shaoping Ma:
Explicit factor models for explainable recommendation based on phrase-level sentiment analysis. SIGIR 2014: 83-92
Coauthor Index
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