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Towards Teachable Reasoning Systems. (arXiv:2204.13074v1 [cs.CL])
April 28, 2022, 1:11 a.m. | Bhavana Dalvi, Oyvind Tafjord, Peter Clark
cs.CL updates on arXiv.org arxiv.org
Our goal is a teachable reasoning system for question-answering (QA), where a
user can interact with faithful answer explanations, and correct errors so that
the system improves over time. Our approach is three-fold: First, generated
chains of reasoning show how answers are implied by the system's own internal
beliefs. Second, users can interact with the explanations to identify erroneous
model beliefs and provide corrections. Third, we augment the model with a
dynamic memory of such corrections. Retrievals from memory are …
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