Zobrazeno 1 - 9
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pro vyhledávání: '"lin, tianqianjin"'
Autor:
Lin, Tianqianjin, Yan, Pengwei, Song, Kaisong, Jiang, Zhuoren, Kang, Yangyang, Lin, Jun, Yuan, Weikang, Cao, Junjie, Sun, Changlong, Liu, Xiaozhong
Graph foundation models (GFMs) have recently gained significant attention. However, the unique data processing and evaluation setups employed by different studies hinder a deeper understanding of their progress. Additionally, current research tends t
Externí odkaz:
http://arxiv.org/abs/2410.14961
Autor:
Yuan, Weikang, Cao, Junjie, Jiang, Zhuoren, Kang, Yangyang, Lin, Jun, Song, Kaisong, lin, tianqianjin, Yan, Pengwei, Sun, Changlong, Liu, Xiaozhong
Large Language Models (LLMs) could struggle to fully understand legal theories and perform complex legal reasoning tasks. In this study, we introduce a challenging task (confusing charge prediction) to better evaluate LLMs' understanding of legal the
Externí odkaz:
http://arxiv.org/abs/2410.02507
Autor:
Yan, Pengwei, Song, Kaisong, Jiang, Zhuoren, Kang, Yangyang, Lin, Tianqianjin, Sun, Changlong, Liu, Xiaozhong
While self-supervised graph pretraining techniques have shown promising results in various domains, their application still experiences challenges of limited topology learning, human knowledge dependency, and incompetent multi-level interactions. To
Externí odkaz:
http://arxiv.org/abs/2312.11927
Autor:
Lin, Tianqianjin, Song, Kaisong, Jiang, Zhuoren, Kang, Yangyang, Yuan, Weikang, Li, Xurui, Sun, Changlong, Huang, Cui, Liu, Xiaozhong
Publikováno v:
Information Processing & Management, 60 (2024) 1-21
Heterogeneous graph neural networks have become popular in various domains. However, their generalizability and interpretability are limited due to the discrepancy between their inherent inference flows and human reasoning logic or underlying causal
Externí odkaz:
http://arxiv.org/abs/2312.05757
Autor:
Lin, Tianqianjin, Song, Kaisong, Jiang, Zhuoren, Kang, Yangyang, Yuan, Weikang, Li, Xurui, Sun, Changlong, Huang, Cui, Liu, Xiaozhong
Publikováno v:
In Information Processing and Management March 2024 61(2)
Autor:
Lin, Tianqianjin1 lintqj@zju.edu.cn, Wang, Qian2 qwang18@wpi.edu, Jiang, Zhuoren1 jiangzhuoren@zju.edu.cn, Yuan, Weikang1 yuanwk@zju.edu.cn, Huang, Cui1 huangcui@zju.edu.cn, Mabry, Patricia3 patricia.l.mabry@healthpartners.com, Liu, Xiaozhong2 xliu14@wpi.edu
Publikováno v:
Proceedings of the Association for Information Science & Technology. Oct2023, Vol. 60 Issue 1, p651-655. 5p.
Publikováno v:
In Journal of Informetrics February 2023 17(1)
Publikováno v:
In Government Information Quarterly January 2021 38(1)
Autor:
Jiang, Tingting1 tij@whu.edu.cn, Lin, Tianqianjin1 lintqj@whu.edu.cn, Shangguan, Lina2 sgln@whu.edu.cn, Wang, Ying1 wy1210@whu.edu.cn
Publikováno v:
Proceedings of the Association for Information Science & Technology. 2019, Vol. 56 Issue 1, p679-681. 3p.