Generative Models for Complex Logical Reasoning over Knowledge Graphs-Reference-Cited by-同舟云学术

Generative Models for Complex Logical Reasoning over Knowledge Graphs

Published:2024-03-04 Issue: Volume:33 Page:492-500
ISSN:
Container-title:Proceedings of the 17th ACM International Conference on Web Search and Data Mining
language:
Short-container-title:

Author:

Liu Yu¹^ORCID,Cao Yanan¹^ORCID,Wang Shi²^ORCID,Wang Qingyue¹^ORCID,Bi Guanqun¹^ORCID

Affiliation:

1. Institute of Information Engineering, Chinese Academy of Sciences & School of Cyber Security, University of Chinese Academy of Sciences, Beijing, China

2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

Funder

National Key Research and Development Program of China

Strategic Priority Research Program of the Chinese Academy of Sciences

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3616855.3635804

Reference50 articles.

1. Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, and Ce Zhang. 2022. Neural Methods for Logical Reasoning over Knowledge Graphs.. In Proceedings of the Tenth International Conference on Learning Representations.

2. Erik Arakelyan, Daniel Daza, Pasquale Minervini, and Michael Cochez. 2021. Complex query answering with neural link predictors. Proceedings of the Ninth International Conference on Learning Representations (2021).

3. Guanqun Bi, Lei Shen, Yanan Cao, Meng Chen, Yuqiang Xie, Zheng Lin, and Xiaodong He. 2023. DiffusEmp: A Diffusion Model-Based Framework with Multi-Grained Control for Empathetic Response Generation. arXiv preprint arXiv:2306.01657 (2023).

4. Zhen Bi, Siyuan Cheng, Ningyu Zhang, Xiaozhuan Liang, Feiyu Xiong, and Huajun Chen. 2022. Relphormer: Relational Graph Transformer for Knowledge Graph Representation. arXiv preprint arXiv:2205.10852 (2022).

5. Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. Advances in neural information processing systems 26 (2013).