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most citedAdaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity

10 citations · 18 across the 28 of their papers we have counts for

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cs.CV2025

VideoRAG: Retrieval-Augmented Generation over Video Corpus

Soyeong Jeong, Kangsan Kim, Jinheon Baek +1

Retrieval-Augmented Generation (RAG) is a powerful strategy for improving the factual accuracy of models by retrieving external knowledge relevant to queries and incorporating it i…

cs.CV2024

CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73

Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…