Papers with implicit multi-hop reasoning

2 papers
Differentiable Open-Ended Commonsense Reasoning (2021.naacl-main)

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Challenge: Existing commonsense reasoning models work by scoring a question-candidate pair, but new approaches are needed to answer multiple-choice questions.
Approach: They propose to use a corpus of commonsense facts to answer a commonsensical question without any pre-defined choices as a resource.
Outcome: The proposed model outperforms baseline methods by a large margin in the open-ended commonsense reasoning task.
Open-ended Commonsense Reasoning with Unrestricted Answer Candidates (2023.findings-emnlp)

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Challenge: Current approaches to commonsense reasoning are limited due to limited answer scope.
Approach: They propose to solve a commonsense question without a pre-defined answer scope . they leverage pre-trained language models to iteratively retrieve reasoning paths on the external knowledge base .
Outcome: The proposed method achieves better performance on two commonsense benchmark datasets.

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