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APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning., , , , , , , and . ACL (1), page 6308-6321. Association for Computational Linguistics, (2023)A Hierarchical and Distributed Approach for Mapping Large Applications to Heterogeneous Grids Using Genetic Algorithms., , , and . CLUSTER, page 496-499. IEEE Computer Society, (2003)Composition-based Multi-Relational Graph Convolutional Networks., , , and . ICLR, OpenReview.net, (2020)MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction., , , , , , and . CoRR, (2018)InteractE: Improving Convolution-Based Knowledge Graph Embeddings by Increasing Feature Interactions., , , , and . AAAI, page 3009-3016. AAAI Press, (2020)Discretized Integrated Gradients for Explaining Language Models., and . EMNLP (1), page 10285-10299. Association for Computational Linguistics, (2021)SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning., , , , , and . NeurIPS, page 18241-18255. (2021)PlaSma: Procedural Knowledge Models for Language-based Planning and Re-Planning., , , , , , , , , and . ICLR, OpenReview.net, (2024)Generate rather than Retrieve: Large Language Models are Strong Context Generators., , , , , , , , and . ICLR, OpenReview.net, (2023)Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verification., , , , and . ACL (Findings), page 10361-10386. Association for Computational Linguistics, (2024)