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Zecheng Wang
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2020 – today
- 2024
- [c9]Zecheng Wang, Chunshan Li, Zhao Yang, Qingbin Liu, Yanchao Hao, Xi Chen, Dianhui Chu, Dianbo Sui:
Analyzing Chain-of-thought Prompting in Black-Box Large Language Models via Estimated V-information. LREC/COLING 2024: 893-903 - [c8]Deyuan Liu, Zhanyue Qin, Hairu Wang, Zhao Yang, Zecheng Wang, Fangying Rong, Qingbin Liu, Yanchao Hao, Bo Li, Xi Chen, Cunhang Fan, Zhao Lv, Dianhui Chu, Zhiying Tu, Dianbo Sui:
Pruning via Merging: Compressing LLMs via Manifold Alignment Based Layer Merging. EMNLP 2024: 17817-17829 - [c7]Zecheng Wang, Che Wang, Zixuan Dong, Keith W. Ross:
Pre-training with Synthetic Data Helps Offline Reinforcement Learning. ICLR 2024 - [c6]Zecheng Wang, Xinye Li, Zhanyue Qin, Chunshan Li, Zhiying Tu, Dianhui Chu, Dianbo Sui:
Can We Debias Multimodal Large Language Models via Model Editing? ACM Multimedia 2024: 3219-3228 - [c5]Yufei Li, Chunshan Li, Zecheng Wang, Dianbo Sui, Jianen Yan:
A Privacy-Preserving Framework for Medical Chatbot Based on LLM with Retrieval Augmented Generation. NLPCC (3) 2024: 15-28 - [i6]Deyuan Liu, Zecheng Wang, Bingning Wang, Weipeng Chen, Chunshan Li, Zhiying Tu, Dianhui Chu, Bo Li, Dianbo Sui:
Checkpoint Merging via Bayesian Optimization in LLM Pretraining. CoRR abs/2403.19390 (2024) - [i5]Deyuan Liu, Zhanyue Qin, Hairu Wang, Zhao Yang, Zecheng Wang, Fangying Rong, Qingbin Liu, Yanchao Hao, Xi Chen, Cunhang Fan, Zhao Lv, Zhiying Tu, Dianhui Chu, Dianbo Sui:
Pruning via Merging: Compressing LLMs via Manifold Alignment Based Layer Merging. CoRR abs/2406.16330 (2024) - [i4]Zhanyue Qin, Haochuan Wang, Zecheng Wang, Deyuan Liu, Cunhang Fan, Zhao Lv, Zhiying Tu, Dianhui Chu, Dianbo Sui:
Mitigating Gender Bias in Code Large Language Models via Model Editing. CoRR abs/2410.07820 (2024) - 2023
- [j6]Linjun Huang, Han Song, Zecheng Wang, Hongzhe Li, Delong Ma, Peng Yu:
The Study of 2-D Magnetic Focusing Inversion Based on the Adjustable Exponential Minimum Support Stabilizing Functional. IEEE Trans. Geosci. Remote. Sens. 61: 1-10 (2023) - [c4]Zecheng Wang, Yik-Cheung Tam:
Suffix Retrieval-Augmented Language Modeling. ICASSP 2023: 1-5 - [i3]Zecheng Wang, Che Wang, Zixuan Dong, Keith W. Ross:
Pre-training with Synthetic Data Helps Offline Reinforcement Learning. CoRR abs/2310.00771 (2023) - 2022
- [j5]Zecheng Wang, Huaizhong Bao, Tao Zhao, Faze Du, Xuemin Chen:
New Lattice-Based Short Proxy Signature Scheme With Fewer System Parameters in the Standard Model. IEEE Access 10: 57180-57191 (2022) - [c3]Yik-Cheung Tam, Jiacheng Xu, Jiakai Zou, Zecheng Wang, Tinglong Liao, Shuhan Yuan:
Robust Unstructured Knowledge Access in Conversational Dialogue with ASR Errors. ICASSP 2022: 6702-6706 - [i2]Zecheng Wang, Yik-Cheung Tam:
Suffix Retrieval-Augmented Language Modeling. CoRR abs/2211.03053 (2022) - [i1]Yik-Cheung Tam, Jiacheng Xu, Jiakai Zou, Zecheng Wang, Tinglong Liao, Shuhan Yuan:
Robust Unstructured Knowledge Access in Conversational Dialogue with ASR Errors. CoRR abs/2211.03990 (2022) - 2021
- [c2]Zecheng Wang, Geng Zhang, Bingliang Hu:
Generic Demosaicking Method for Multispectral Filter Arrays Based on Adaptive Frequency Domain Filtering. SSIP 2021: 66-71
2010 – 2019
- 2017
- [j4]Zecheng Wang, Xuemin Chen, Pingshui Wang:
Adaptive-ID Secure Identity-Based Signature Scheme from Lattices in the Standard Model. IEEE Access 5: 20791-20799 (2017)
2000 – 2009
- 2009
- [j3]Zecheng Wang, Haifeng Qian, Zhibin Li:
Adaptively Secure Threshold Signature Scheme in the Standard Model. Informatica 20(4): 591-612 (2009) - 2008
- [j2]Haifeng Qian, Yuan Zhou, Zhibin Li, Zecheng Wang, Bing Zhang:
Efficient public key encryption with smallest ciphertext expansion from factoring. Des. Codes Cryptogr. 49(1-3): 233-249 (2008) - [c1]Zecheng Wang, Taozhi Si, Haifeng Qian, Zhibin Li:
A CDH-Based Multi-Signature Scheme with Tight Security Reduction. ICYCS 2008: 2096-2101 - 2007
- [j1]Zecheng Wang, Haifeng Qian, Zhibin Li:
Hybrid proxy multisignature: A new type multi-party signature. Inf. Sci. 177(24): 5638-5650 (2007)
Coauthor Index
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last updated on 2024-11-18 20:47 CET by the dblp team
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