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cs.CV2024
VLR-Bench: Multilingual Benchmark Dataset for Vision-Language Retrieval Augmented Generation
Hyeonseok Lim, Dongjae Shin, Seohyun Song +5
We propose the VLR-Bench, a visual question answering (VQA) benchmark for evaluating vision language models (VLMs) based on retrieval augmented generation (RAG). Unlike existing ev…
cs.CL2024
X-LLaVA: Optimizing Bilingual Large Vision-Language Alignment
Dongjae Shin, Hyeonseok Lim, Inho Won +6
The impressive development of large language models (LLMs) is expanding into the realm of large multimodal models (LMMs), which incorporate multiple types of data beyond text. Howe…
cs.CL2024
BOK-VQA: Bilingual outside Knowledge-Based Visual Question Answering via Graph Representation Pretraining
Minjun Kim, Seungwoo Song, Youhan Lee +2
The current research direction in generative models, such as the recently developed GPT4, aims to find relevant knowledge information for multimodal and multilingual inputs to prov…