adaptive-data-refinement-vlm-long-tail

Mitigate long-tail distribution problems in VLM training data through adaptive rebalancing and diffusion-based synthesis. Uses entity distribution analysis to identify head/tail imbalance and applies targeted data augmentation, improving LLaVA 1.5 performance by 4.36% without increasing training data volume.

Independent GitHub snapshot · Automated classification · Original documentation governs