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ORCIDJiawei Liu 0006
Person information
- unicode name: 刘佳玮
- affiliation: Beijing University of Posts and Telecommunications, Beijing, China
Other persons with the same name
- Jiawei Liu — disambiguation page
- Jiawei Liu 0001
![[0000-0001-9940-6366]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-9940-6366")
— University of Science and Technology of China, Department of Information and Intelligence, Hefei, China - Jiawei Liu 0002 — Wuhan University, Wuhan, Hubei, China
- Jiawei Liu 0003 — Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
- Jiawei Liu 0004 — University of Illinois at Urbana-Champaign, IL, USA
- Jiawei Liu 0005 — Australian National University, Canberra, ACT, Australia
- Jiawei Liu 0007 — University of Science and Technology of China, School of Computer Science and Technology, Hefei, China
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2020 – today
- 2025
[j5]Jiawei Liu, Wenyi Xiao, Hongtao Cheng, Chuan Shi:
Graph neural network based time estimator for SAT solver. Int. J. Mach. Learn. Cybern. 16(2): 1145-1156 (2025)- [j4]Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi:
Graph Foundation Models: Concepts, Opportunities and Challenges. IEEE Trans. Pattern Anal. Mach. Intell. 47(6): 5023-5044 (2025) - [c13]Feng Guo, Yueyue Xi, Jianwang Zhai, Jingyu Jia, Jiawei Liu, Kang Zhao, Chuan Shi:
IRGNN: A Graph-based Framework Integrating Numerical Solution and Point Cloud for Static IR Drop Prediction. DAC 2025: 1-7 - [c12]Feng Guo, Jianwang Zhai, Jingyu Jia, Jiawei Liu, Kang Zhao, Bei Yu, Chuan Shi:
IR-Fusion: A Fusion Framework for Static IR Drop Analysis Combining Numerical Solution and Machine Learning. DATE 2025: 1-7 - [c11]Jiawei Liu, Zhiyan Liu, Xun He, Jianwang Zhai, Zhengyuan Shi, Qiang Xu, Bei Yu, Chuan Shi:
WideGate: Beyond Directed Acyclic Graph Learning in Subcircuit Boundary Prediction. DATE 2025: 1-7 - [c10]Mingyu Zhao, Jiawei Liu, Jianwang Zhai, Chuan Shi:
MILS: Modality Interaction Driven Learning for Logic Synthesis. ACM Great Lakes Symposium on VLSI 2025: 64-70 - [i14]Jiawei Liu, Yuanzhi Zhu, Feiyu Gao, Zhibo Yang, Peng Wang, Junyang Lin, Xinggang Wang, Wenyu Liu:
SceneVTG++: Controllable Multilingual Visual Text Generation in the Wild. CoRR abs/2501.02962 (2025) - [i13]Bin Wu, Yihang Wang, Yuanhao Zeng, Jiawei Liu, Jiashu Zhao, Cheng Yang, Yawen Li, Long Xia, Dawei Yin, Chuan Shi:
Graph Foundation Models for Recommendation: A Comprehensive Survey. CoRR abs/2502.08346 (2025) - [i12]Zhengyuan Shi, Zeju Li, Chengyu Ma, Yunhao Zhou, Ziyang Zheng, Jiawei Liu, Hongyang Pan, Lingfeng Zhou, Kezhi Li, Jiaying Zhu, Lingwei Yan, Zhiqiang He, Chenhao Xue, Wentao Jiang, Fan Yang, Guangyu Sun, Xiaoyan Yang, Gang Chen, Chuan Shi, Zhufei Chu, Jun Yang, Qiang Xu:
ForgeEDA: A Comprehensive Multimodal Dataset for Advancing EDA. CoRR abs/2505.02016 (2025) - [i11]Shan Shen, Shenglu Hua, Jiajun Zou, Jiawei Liu, Jianwang Zhai, Chuan Shi, Wenjian Yu:
Transferable Parasitic Estimation via Graph Contrastive Learning and Label Rebalancing in AMS Circuits. CoRR abs/2507.06535 (2025) - 2024
- [j3]Chuan Shi, Junze Chen, Jiawei Liu, Cheng Yang:
Graph foundation model. Frontiers Comput. Sci. 18(6): 186355 (2024) - [j2]Zhenyang Hao, Xinggang Wang, Jiawei Liu, Zhihang Yuan, Dawei Yang, Wenyu Liu:
Stabilized activation scale estimation for precise Post-Training Quantization. Neurocomputing 569: 127120 (2024) - [c9]Yuanzhi Zhu, Jiawei Liu, Feiyu Gao, Wenyu Liu, Xinggang Wang, Peng Wang, Fei Huang, Cong Yao, Zhibo Yang:
Visual Text Generation in the Wild. ECCV (53) 2024: 89-106 - [c8]Feng Guo, Jiawei Liu, Jianwang Zhai, Jingyu Jia, Kang Zhao, Chuan Shi:
PGAU: Static IR Drop Analysis for Power Grid using Attention U-Net Architecture and Label Distribution Smoothing. ACM Great Lakes Symposium on VLSI 2024: 452-458 - [c7]Jiawei Liu, Jianwang Zhai, Mingyu Zhao, Zhe Lin, Bei Yu, Chuan Shi:
PolarGate: Breaking the Functionality Representation Bottleneck of And-Inverter Graph Neural Network. ICCAD 2024: 185:1-185:9 - [c6]Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi:
Endowing Pre-trained Graph Models with Provable Fairness. WWW 2024: 1045-1056 - [i10]Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi:
Endowing Pre-trained Graph Models with Provable Fairness. CoRR abs/2402.12161 (2024) - [i9]Yuanzhi Zhu, Jiawei Liu, Feiyu Gao, Wenyu Liu, Xinggang Wang, Peng Wang, Fei Huang, Cong Yao, Zhibo Yang:
Visual Text Generation in the Wild. CoRR abs/2407.14138 (2024) - 2023
- [c5]Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu:
PD-Quant: Post-Training Quantization Based on Prediction Difference Metric. CVPR 2023: 24427-24437 - [c4]Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang:
Abnormal Event Detection via Hypergraph Contrastive Learning. SDM 2023: 712-720 - [c3]Cheng Yang, Yuxin Guo, Yao Xu, Chuan Shi, Jiawei Liu, Chunchen Wang, Xin Li, Ning Guo, Hongzhi Yin:
Learning to Distill Graph Neural Networks. WSDM 2023: 123-131 - [i8]Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu:
Benchmarking the Reliability of Post-training Quantization: a Particular Focus on Worst-case Performance. CoRR abs/2303.13003 (2023) - [i7]Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu:
RPTQ: Reorder-based Post-training Quantization for Large Language Models. CoRR abs/2304.01089 (2023) - [i6]Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang:
Abnormal Event Detection via Hypergraph Contrastive Learning. CoRR abs/2304.01226 (2023) - [i5]Lin Niu, Jiawei Liu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu:
Improving Post-Training Quantization on Object Detection with Task Loss-Guided Lp Metric. CoRR abs/2304.09785 (2023) - [i4]Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi:
Towards Graph Foundation Models: A Survey and Beyond. CoRR abs/2310.11829 (2023) - 2022
- [j1]Jiawei Liu, Chuan Shi, Cheng Yang, Zhiyuan Lu, Philip S. Yu:
A survey on heterogeneous information network based recommender systems: Concepts, methods, applications and resources. AI Open 3: 40-57 (2022) - [i3]Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu:
PD-Quant: Post-Training Quantization based on Prediction Difference Metric. CoRR abs/2212.07048 (2022) - 2021
- [c2]Cheng Yang, Jiawei Liu, Chuan Shi:
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework. WWW 2021: 1227-1237 - [i2]Cheng Yang, Jiawei Liu, Chuan Shi:
Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework. CoRR abs/2103.02885 (2021) - 2020
- [c1]Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang:
Decorrelated Clustering with Data Selection Bias. IJCAI 2020: 2177-2183 - [i1]Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang:
Decorrelated Clustering with Data Selection Bias. CoRR abs/2006.15874 (2020)
Coauthor Index
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last updated on 2025-10-02 01:20 CEST by the dblp team
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