Papers by Nir Mazor
LVLM-Aware Multimodal Retrieval for RAG-Based Medical Diagnosis with General-Purpose Models (2026.findings-acl)
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| Challenge: | Using retrieval augmentation, large vision language models can be used for diagnostic accuracy, but multimodal retrieval-augmented diagnosis is challenging. |
| Approach: | They propose a lightweight mechanism for enhancing diagnostic performance of retrieval-augmented LVLMs by fine-tuning a multimodal retriever and general-purpose backbone models. |
| Outcome: | The proposed mechanism achieves competitive results without medical training compared to pre-trained models with extensive training. |
More Documents, Same Length: Isolating the Challenge of Multiple Documents in RAG (2025.findings-emnlp)
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| Challenge: | Retrieval-Augmented Generation (RAG) enhances the accuracy of Large Language Models by leveraging relevant external documents during generation. |
| Approach: | They evaluate various language models on custom datasets derived from QA tasks . they keep context length and position of relevant information constant while varying the number of documents . |
| Outcome: | The proposed method improves the accuracy of large language models by leveraging external documents . increasing document count reduces performance by up to 20%, the authors find . |