Genixer: Empowering Multimodal Large Language Models as a Powerful Data Generator

arXiv:2312.06731v2 Announce Type: replace
Abstract: Instruction tuning data is essential for training the Multimodal Large Language Models (MLLMs). However, the creation of high-quality instruction tuning data presents significant challenges. Prior methods that depended on GPT-4 for data generation were not only costly but also lacked satisfactory performance in complex tasks (i.e., grounding-based reasoning tasks). To address these issues, we developed an innovative data generation pipeline, Genixer, to generate various high-quality instruction tuning data, including nine representative tasks, e.g., Common VQA, …

abstract arxiv challenges cs.ai cs.cv data generator gpt gpt-4 however language language models large language large language models mllms multimodal performance prior quality training type