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Probing Structured Semantics Understanding and Generation of Language Models via Question Answering
Extensive experiments with models of different sizes and in different formal languages show that today's state-of-the-art LLMs' understanding of the logical forms can approach human level overall, but there still are plenty of room in generating correct logical forms, which suggest that it is more effective to use LLMs to generate more natural language training data to reinforce a small model than directly answering questions with LLMs.
EDUKG: a Heterogeneous Sustainable K-12 Educational Knowledge Graph
To tackle these issues, we propose EDUKG, a heterogeneous sustainable K-12 Educational Knowledge Graph.
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