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Complex query answering (CQA) on knowledge graphs (KGs) is gaining momentum as a challenging reasoning task.
Freebase: a collaboratively created graph database for structuring human knowledge
Bollacker, K. D., Evans, C., Paritosh, P. K., Sturge, T., and Taylor, J · 2008
Earlier work this paper cites.
Toward an architecture for never-ending language learning
Carlson, A., Betteridge, J., Kisiel, B., Settles, B., Jr., E. R. H., and Mitchell, T. M · 2010
Earlier work this paper cites.
The dichotomy of probabilistic inference for unions of conjunctive queries
Dalvi, N. N. and Suciu, D · 2012
Earlier work this paper cites.
Translating embeddings for modeling multi-relational data
Bordes, A., Usunier, N., García-Durán, A., Weston, J., and Yakhnenko, O · 2013
Earlier work this paper cites.
Reducing the rank in relational factorization models by including observable patterns
Nickel, M., Jiang, X., and Tresp, V · 2014
Earlier work this paper cites.
ICEWS Coded Event Data, 2015
Boschee, E., Lautenschlager, J., O’Brien, S., Shellman, S., Starz, J., and Ward, M · 2015
Earlier work this paper cites.
Traversing knowledge graphs in vector space
Guu, K., Miller, J., and Liang, P · 2015
Earlier work this paper cites.
Observed versus latent features for knowledge base and text inference
Toutanova, K. and Chen, D · 2015
Earlier work this paper cites.
Knowledge graph completion via complex tensor factorization
Trouillon, T., Dance, C. R., Gaussier, É., Welbl, J., Riedel, S., and Bouchard, G · 2017
Earlier work this paper cites.
Deeppath: A reinforcement learning method for knowledge graph reasoning
Xiong, W., Hoang, T., and Wang, W. Y · 2017
Earlier work this paper cites.
Embedding logical queries on knowledge graphs
Hamilton, W. L., Bajaj, P., Zitnik, M., Jurafsky, D., and Leskovec, J · 2018
Earlier work this paper cites.
Sparql query language
Hogan, A · 2020
Earlier work this paper cites.
Beta embeddings for multi-hop logical reasoning in knowledge graphs
Ren, H. and Leskovec, J · 2020
Cited alongside, same era.
Query2box: Reasoning over knowledge graphs in vector space using box embeddings
Ren, H., Hu, W., and Leskovec, J · 2020
Cited alongside, same era.
You CAN teach an old dog new tricks! on training knowledge graph embeddings
Ruffinelli, D., Broscheit, S., and Gemulla, R · 2020
Cited alongside, same era.
Faithful embeddings for knowledge base queries
Sun, H., Arnold, A. O., Bedrax-Weiss, T., Pereira, F., and Cohen, W. W · 2020
Cited alongside, same era.
Complex query answering with neural link predictors
Arakelyan, E., Daza, D., Minervini, P., and Cochez, M · 2021
Cited alongside, same era.
Self-supervised hyperboloid representations from logical queries over knowledge graphs
Choudhary, N., Rao, N., Katariya, S., Subbian, K., and Reddy, C. K · 2021
Neural-symbolic models for logical queries on knowledge graphs
Zhu, Z., Galkin, M., Zhang, Z., and Tang, J · 2022
Later among the works it cites.
Adapting neural link predictors for data-efficient complex query answering
Arakelyan, E., Minervini, P., Daza, D., Cochez, M., and Augenstein, I · 2023
Later among the works it cites.
Answering complex logical queries on knowledge graphs via query computation tree optimization
Bai, Y., Lv, X., Li, J., and Hou, L · 2023
Later among the works it cites.
How to turn your knowledge graph embeddings into generative models
Loconte, L., Di Mauro, N., Peharz, R., and Vergari, A · 2023
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Neural graph reasoning: Complex logical query answering meets graph databases
Ren, H., Galkin, M., Cochez, M., Zhu, Z., and Leskovec, J · 2023
Later among the works it cites.
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Cited alongside, same era.
Knowledge graphs
Hogan, A., Blomqvist, E., Cochez, M., d’Amato, C., Melo, G. D., Gutierrez, C., Kirrane, S., Gayo, J. E. L., Navigli, R., Neumaier, S., et al · 2021
Cited alongside, same era.
Cone: Cone embeddings for multi-hop reasoning over knowledge graphs
Zhang, Z., Wang, J., Chen, J., Ji, S., and Wu, F · 2021
Cited alongside, same era.
Fuzzy logic based logical query answering on knowledge graphs
Chen, X., Hu, Z., and Sun, Y · 2022
Cited alongside, same era.
Inductive logical query answering in knowledge graphs
Galkin, M., Zhu, Z., Ren, H., and Tang, J · 2022
Cited alongside, same era.
Analyzing differentiable fuzzy logic operators
van Krieken, E., Acar, E., and van Harmelen, F · 2022
Cited alongside, same era.
Towards foundation models for knowledge graph reasoning
Galkin, M., Yuan, X., Mostafa, H., Tang, J., and Zhu, Z
Cited in the paper.
Logical message passing networks with one-hop inference on atomic formulas
Wang, Z., Song, Y., Wong, G. Y., and See, S · 2023
Later among the works it cites.
E F O k EFO_{k} -cqa: Towards knowledge graph complex query answering beyond set operation
Yin, H., Wang, Z., Fei, W., and Song, Y · 2023
Later among the works it cites.
Rethinking complex queries on knowledge graphs with neural link predictors
Yin, H., Wang, Z., and Song, Y · 2024
Closest in time.
Conditional logical message passing transformer for complex query answering
Zhang, C., Peng, Z., Zheng, J., and Ma, Q · 2024
Closest in time.
Semma: A semantic aware knowledge graph foundation model, 2025
Arun, A., Kumar, S., Nayyeri, M., Xiong, B., Kumaraguru, P., Vergari, A., and Staab, S · 2025
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Dage: Dag query answering via relational combinator with logical constraints
He, Y., Xiong, B., Hernández, D., Zhu, Y., Kharlamov, E., and Staab, S · 2025
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