Papers with RAG mechanisms

2 papers
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.
Eliciting Critical Reasoning in Retrieval-Augmented Generation via Contrastive Explanations (2025.naacl-long)

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Challenge: Recent studies show that LLMs struggle to critically analyse RAG-based in-context information.
Approach: They propose a framework that elicits critical arguments in RAG via contrastive explanations . they propose CRAG to retrieve relevant documents given a query and generate explanations that explicitly contrast relevance of passages to support the final answer.
Outcome: The proposed framework improves state-of-the-art RAG models while requiring significantly fewer prompts and demonstrations and robust to perturbations in the retrieved documents.

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