Papers with Abductive
COGEN: Abductive Commonsense Language Generation (2023.acl-short)
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| Challenge: | Existing training methods for NLP models to perform on two main tasks are needed to introduce these capabilities into the field of reasoning. |
| Approach: | They propose a model that integrates commonsense reasoning with contextual filtering to improve the inference. |
| Outcome: | The proposed model outperforms existing models and sets new state-of-the-art in regards to alphaNLI and alphaNGG tasks. |
Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning (2020.emnlp-main)
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Lianhui Qin, Vered Shwartz, Peter West, Chandra Bhagavatula, Jena D. Hwang, Ronan Le Bras, Antoine Bosselut, Yejin Choi
| Challenge: | Existing methods for integrating past and future contexts are limited and require manual input. |
| Approach: | They propose an unsupervised decoding algorithm that incorporates past and future contexts using off-the-shelf, left-to-right language models and no supervision. |
| Outcome: | The proposed method outperforms unsupervised methods on abductive and counterfactual reasoning tasks. |