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Combining Extraction and Generation for Constructing Belief-Consequence Causal Links
In this paper, we introduce and justify a new task—causal link extraction based on beliefs—and do a qualitative analysis of the ability of a large language model—InstructGPT-3—to generate implicit consequences of beliefs.
MathAlign: Linking Formula Identifiers to their Contextual Natural Language Descriptions
Extending machine reading approaches to extract mathematical concepts and their descriptions is useful for a variety of tasks, ranging from mathematical information retrieval to increasing accessibility of scientific documents for the visually impaired.
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