Your Vision-Language Model Itself Is a Strong Filter: Towards High-Quality Instruction Tuning with Data Selection (2024.findings-acl)
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Ruibo Chen, Yihan Wu, Lichang Chen, Guodong Liu, Qi He, Tianyi Xiong, Chenxi Liu, Junfeng Guo, Heng Huang
| Challenge: | Existing data selection methods for instruction-following large language models rely on unreliable scores or use downstream tasks for selection. |
| Approach: | They propose a method that utilizes the VLM itself as a filter to select high-quality instruction-tuning data. |
| Outcome: | The proposed method can reach better results compared to full data settings with merely about 15% samples and can achieve superior performance against competitive baselines. |
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