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LaVy: Vietnamese Multimodal Large Language Model

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arxiv 2404.07922 v6 pith:HLX4Z74K submitted 2024-04-11 cs.CL cs.CVcs.LG

classification cs.CLcs.CVcs.LG
keywords languagevietnameselargelavymllmsmodelsmultimodalabilities
verification ladder T0 review T1 audit T2 compute T3 formal
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Large Language Models (LLMs) and Multimodal Large language models (MLLMs) have taken the world by storm with impressive abilities in complex reasoning and linguistic comprehension. Meanwhile there are plethora of works related to Vietnamese Large Language Models, the lack of high-quality resources in multimodality limits the progress of Vietnamese MLLMs. In this paper, we pioneer in address this by introducing LaVy, a state-of-the-art Vietnamese MLLM, and we also introduce LaVy-Bench benchmark designated for evaluating MLLMs's understanding on Vietnamese visual language tasks. Our project is public at https://github.com/baochi0212/LaVy

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Cited by 1 Pith paper

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  1. Parameter Efficient Multimodal Instruction Tuning for Romanian Vision Language Models

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    A new Romanian Flickr30k translation plus synthetic VQA corpus, and LoRA-fine-tuned VLMs that improve Romanian VQA and captioning for LLaMA-3.2 and Qwen2-VL, but not LLaVA-1.6.

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