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- W3213141204 abstract "Defeasible reasoning is the mode of reasoning where conclusions can be overturned by taking into account new evidence. Existing cognitive science literature on defeasible reasoning suggests that a person forms a “mental model” of the problem scenario before answering questions. Our research goal asks whether neural models can similarly benefit from envisioning the question scenario before answering a defeasible query. Our approach is, given a question, to have a model first create a graph of relevant influences, and then leverage that graph as an additional input when answering the question. Our system, CURIOUS, achieves a new state-of-the-art on three different defeasible reasoning datasets. This result is significant as it illustrates that performance can be improved by guiding a system to “think about” a question and explicitly model the scenario, rather than answering reflexively." @default.
- W3213141204 created "2021-11-22" @default.
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- W3213141204 date "2021-10-24" @default.
- W3213141204 modified "2023-10-18" @default.
- W3213141204 title "Think about it! Improving defeasible reasoning by first modeling the question scenario" @default.
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