no code implementations • 17 Jan 2024 • Zhiming Li, Yushi Cao, Xiufeng Xu, Junzhe Jiang, Xu Liu, Yon Shin Teo, Shang-Wei Lin, Yang Liu
Large language models (LLMs) have revolutionized many areas (e. g. natural language processing, software engineering, etc.)
no code implementations • 20 Nov 2023 • Jie Chen, Zhiming Li, Hua Mao, Wai Lok Woo, Xi Peng
In this paper, we propose a cross-view graph consistency learning (CGCL) method that learns invariant graph representations for link prediction.
no code implementations • 9 Oct 2023 • Zhiming Li, Junzhe Jiang, Yushi Cao, Aixin Cui, Bozhi Wu, Bo Li, Yang Liu, Dongning Sun
Particularly, PST first proposes using a novel symbolic program sketch to embed the abstract human expert knowledge of market trends.
no code implementations • 27 Jun 2023 • Tianlin Li, Qing Guo, Aishan Liu, Mengnan Du, Zhiming Li, Yang Liu
Existing fairness regularization terms fail to achieve decision rationale alignment because they only constrain last-layer outputs while ignoring intermediate neuron alignment.
no code implementations • 27 May 2022 • Yushi Cao, Zhiming Li, Tianpei Yang, Hao Zhang, Yan Zheng, Yi Li, Jianye Hao, Yang Liu
In this paper, we combine the above two paradigms together and propose a novel Generalizable Logic Synthesis (GALOIS) framework to synthesize hierarchical and strict cause-effect logic programs.
no code implementations • 19 Jan 2022 • Zhiming Li, Yanzhou Li, Tianlin Li, Mengnan Du, Bozhi Wu, Yushi Cao, Junzhe Jiang, Yang Liu
We propose a Cond-Idf measurement to interpret this behavior, which quantifies the relatedness of a token with a label and its project-specificness.
no code implementations • 1 Jul 2021 • Zhiming Li, Xiaofei Xie, Haoliang Li, Zhengzi Xu, Yi Li, Yang Liu
Hitherto statistical type inference systems rely thoroughly on supervised learning approaches, which require laborious manual effort to collect and label large amounts of data.
no code implementations • 4 Mar 2021 • Peng Yang, Lin Li, Zhiming Li, Mingmei Xu, Yeyin Zhao, Yuanfang Wu
Radial flow can be directly extracted from the azimuthal distribution of mean transverse rapidity.
Nuclear Theory High Energy Physics - Phenomenology Nuclear Experiment
no code implementations • 11 Nov 2019 • Wenqian Fang, Lihua Fu, Meng Zhang, Zhiming Li
In this study, a novel Seismic U-net InterpolaTor (SUIT) is proposed to preserve the seismic texture information while reconstructing the missing traces.
no code implementations • 14 Aug 2019 • Zhiming Li, Qing Wu, Kun Qian
Specifically, in terms of BLEU-4 and Word Error Rate (WER), our performance has reached 94. 50% and 2. 65% on the redundant test set; 92. 30% and 3. 48% on the purified test set.