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Interpretable Proof Generation via Iterative Backward Reasoning. (arXiv:2205.10714v2 [cs.CL] UPDATED)
May 25, 2022, 1:12 a.m. | Hanhao Qu, Yu Cao, Jun Gao, Liang Ding, Ruifeng Xu
cs.CL updates on arXiv.org arxiv.org
We present IBR, an Iterative Backward Reasoning model to solve the proof
generation tasks on rule-based Question Answering (QA), where models are
required to reason over a series of textual rules and facts to find out the
related proof path and derive the final answer. We handle the limitations of
existed works in two folds: 1) enhance the interpretability of reasoning
procedures with detailed tracking, by predicting nodes and edges in the proof
path iteratively backward from the question; 2) …
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