Improving Multilingual Retrieval-Augmented Language Models through Dialectic Reasoning Argumentations (2025.emnlp-main)
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| Challenge: | Existing approaches to ground large language models (LLMs) with RAGs are limited by the heterogeneity of knowledge retrieved. |
| Approach: | They propose a modular approach guided by Argumentative Explanations that evaluates retrieved information by comparing, contrasting and resolving conflicting perspectives. |
| Outcome: | The proposed framework significantly improves RAG approaches, requiring low-impact computational effort and providing robustness to knowledge perturbations. |
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