FuxiaoLiu/LRV-Instruction
[ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
This project helps large language models (LLMs) that can understand images (multi-modal models) become more reliable. It takes existing image-text datasets, enhances them with detailed instructions and answers, and uses this to train models. The output is an improved model that can more accurately interpret visual information and provide correct responses, which is useful for AI researchers or developers working with these advanced models.
297 stars. No commits in the last 6 months.
Use this if you are a researcher or developer aiming to reduce factual errors or 'hallucinations' in your multi-modal AI models when they interpret images and text.
Not ideal if you are an end-user looking for a ready-to-use application, as this project provides tools and methods for improving underlying AI models rather than a direct consumer product.
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297
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15
Language
Python
License
BSD-3-Clause
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Last pushed
Mar 13, 2024
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