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TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs Julia Gastinger 1,2,6 Shenyang Huang 1,4 Mikhail Galkin
However, the availability of such resources remains scarce and evaluation faces added complexity due to reproducibility issues in experimental protocols.
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MEQA: A Benchmark for Multi-hop Event-centric Question Answering with Explanations
However, there's a lack of insight into how these models perform in terms
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Rehearsal Learning for Avoiding Undesired Future
Machine learning (ML) models have been widely used to make predictions.
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Knowledge Graph Completion by Intermediate Variables Regularization
Existing regularization methods merely minimize the norms of embeddings to regularize the model, leading to suboptimal performance.
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