V-GIFT Boosts Visual Reasoning via Self-Supervised Guidance
srchvrs · x · 2026-08-26
The paper V-GIFT proposes a lightweight method to improve visual instruction tuning by interleaving standard tasks with self-supervised learning (SSL) tasks like rotation prediction. This forces the model to rely on visual evidence rather than language priors. Requiring no architectural changes, adding just 3-10% of visually grounded instructions consistently improves performance on vision-centric benchmarks across multiple models.
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