Papers with multi-hop Question Answering

2 papers
Diff-Explainer: Differentiable Convex Optimization for Explainable Multi-hop Inference (2022.tacl-1)

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Challenge: Existing explainable multi-hop inference models are regarded as black-boxes due to their ability to transfer linguistic and semantic information to downstream tasks, posing concerns about interpretability and transparency of their predictions.
Approach: They propose a hybrid framework that integrates explicit constraints with neural architectures through differentiable convex optimization to answer and explain multi-hop questions in natural language.
Outcome: The proposed framework improves performance on scientific and commonsense QA tasks while still providing structured explanations in support of its predictions.
StepKE: Stepwise Knowledge Editing for Multi-Hop Question Answering (2025.findings-emnlp)

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Challenge: Existing knowledge editing methods overlook interplay with pre-existing knowledge, leading to inconsistent edit propagation.
Approach: stepKE integrates edited and existing knowledge for coherent multi-hop reasoning . stepKE decomposes multi-step questions into sequential single-hop sub-questions .
Outcome: Experiments show that StepKE generates more accurate and consistent responses than baselines.

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