LLMs frequently generate rational plans for multi-step questions but often fail to produce answers, and a new Franklin dataset is especially hard for them.
In Proceedings of the 2019 Con- ference of the North , 4149–4158
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Evaluating the Meta- and Object-Level Reasoning of Large Language Models for Question Answering
LLMs frequently generate rational plans for multi-step questions but often fail to produce answers, and a new Franklin dataset is especially hard for them.