no code implementations • 4 Mar 2024 • Yangbo Jiang, Zhiwei Jiang, Le Han, Zenan Huang, Nenggan Zheng
In this paper, we investigate the statistical moments of feature maps within a neural network.
1 code implementation • 16 Nov 2023 • Yuliang Liu, Xiangru Tang, Zefan Cai, Junjie Lu, Yichi Zhang, Yanjun Shao, Zexuan Deng, Helan Hu, Kaikai An, Ruijun Huang, Shuzheng Si, Sheng Chen, Haozhe Zhao, Liang Chen, Yan Wang, Tianyu Liu, Zhiwei Jiang, Baobao Chang, Yujia Qin, Wangchunshu Zhou, Yilun Zhao, Arman Cohan, Mark Gerstein
While Large Language Models (LLMs) have demonstrated proficiency in code generation benchmarks, translating these results into practical development scenarios - where leveraging existing repository-level libraries is the norm - remains challenging.
no code implementations • 3 Nov 2023 • Tianqi Xiang, Zhiwei Jiang, Weijun Hong, Xin Zhang, Yuehong Gao
In this paper, Reconfigurable Intelligent Surface & Edge (RISE) is proposed to extend RIS' abilities of reflection and refraction over surfaces to diffraction around obstacles' edge for better adaptation to specific coverage scenarios.
1 code implementation • 16 Jul 2023 • Zifeng Cheng, Qingyu Zhou, Zhiwei Jiang, Xuemin Zhao, Yunbo Cao, Qing Gu
However, these methods are only trained at a single granularity (i. e., either token level or span level) and have some weaknesses of the corresponding granularity.
1 code implementation • 1 Mar 2023 • Cong Wang, Zhiwei Jiang, Yafeng Yin, Zifeng Cheng, Shiping Ge, Qing Gu
For deep ordinal classification, learning a well-structured feature space specific to ordinal classification is helpful to properly capture the ordinal nature among classes.
1 code implementation • 16 Apr 2022 • Zifeng Cheng, Zhiwei Jiang, Yafeng Yin, Cong Wang, Qing Gu
In our method, soft labeling is used to reshape the label distribution of the known intent samples, aiming at reducing model's overconfident on known intents.
1 code implementation • COLING 2020 • Zifeng Cheng, Zhiwei Jiang, Yafeng Yin, Hua Yu, Qing Gu
Each subnetwork is composed of a clause representation learner and a local pair searcher.
no code implementations • COLING 2018 • Zhiwei Jiang, Qing Gu, Yafeng Yin, Daoxu Chen
In this paper, we present a method which learns the word embedding for readability assessment.