Papers with CSQA2.0
IAG: Induction-Augmented Generation Framework for Answering Reasoning Questions (2023.emnlp-main)
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| Challenge: | Existing approaches to QA using retrieval-augmented knowledge are limited by limited coverage and noisy information. |
| Approach: | They propose an induction-augmented generation framework that utilizes inductive knowledge along with retrieved documents for implicit reasoning. |
| Outcome: | The proposed framework outperforms RAG and ChatGPT on two Open-Domain QA tasks. |
Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact Verification (2023.findings-acl)
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| Challenge: | Existing studies focus on grasping unstructured evidence or potential reasoning paths from structured knowledge bases, yet failing to exploit the benefits of heterogeneous knowledge simultaneously. |
| Approach: | They propose a commonsense fact verification model that bridging heterogeneous knowledge by uncovering latent relationships between structured and unstructured knowledge. |
| Outcome: | The proposed model can bridge heterogeneous knowledge by uncovering latent relationships between structured and unstructured knowledge. |