受强制性开放获取政策约束的文章 - Zhaoxuan Tan了解详情
可在其他位置公开访问的文章:10 篇
Can Language Models Solve Graph Problems in Natural Language?
H Wang, S Feng, T He, Z Tan, X Han, Y Tsvetkov
NeurIPS 2023, spotlight, 2023
强制性开放获取政策: US National Science Foundation, US Department of Defense
TwiBot-22: Towards graph-based Twitter bot detection
S Feng, Z Tan, H Wan, N Wang, Z Chen, B Zhang, Q Zheng, W Zhang, ...
NeurIPS 2022, Dataset and Benchmark Track, 2022
强制性开放获取政策: 国家自然科学基金委员会
Heterogeneity-aware twitter bot detection with relational graph transformers
S Feng, Z Tan, R Li, M Luo
AAAI 2022, 2022
强制性开放获取政策: 国家自然科学基金委员会
KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion
Z Tan, Z Chen, S Feng, Q Zhang, Q Zheng, J Li, M Luo
The Web Conference 2023, 2022
强制性开放获取政策: 国家自然科学基金委员会
BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts
Y Liu, Z Tan, H Wang, S Feng, Q Zheng, M Luo
SIGIR 2023, 2023
强制性开放获取政策: 国家自然科学基金委员会
Knowledge crosswords: Geometric reasoning over structured knowledge with large language models
W Ding, S Feng, Y Liu, Z Tan, V Balachandran, T He, Y Tsvetkov
ACL 2024, findings, 2023
强制性开放获取政策: US National Science Foundation
LMBot: Distilling Graph Knowledge into Language Model for Graph-less Deployment in Twitter Bot Detection
Z Cai, Z Tan, Z Lei, H Wang, Z Zhu, Q Zheng, M Luo
WSDM 2024, 2023
强制性开放获取政策: 国家自然科学基金委员会
Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples
Q Zeng, Y Bai, Z Tan, S Feng, Z Liang, Z Zhang, M Jiang
CIKM 2024, 2024
强制性开放获取政策: US National Science Foundation, US Department of Defense
AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach
S Yang, B Zhang, S Feng, Z Tan, Q Zheng, J Zhou, M Luo
CIAC 2023, 2022
强制性开放获取政策: 国家自然科学基金委员会
KGQUIZ: Evaluating the Generalization of Encoded Knowledge in Large Language Models
Y Bai, S Feng, V Balachandran, Z Tan, S Lou, T He, Y Tsvetkov
The Web Conference 2024, oral, 2023
强制性开放获取政策: US National Science Foundation, US Department of Defense, US Office of the …
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