Publications by authors named "Minglang Huang"

Article Synopsis
  • Pre-training and fine-tuning are the standard methods for vision-language models, but scaling these models comes with high storage costs and challenges in optimization.
  • Recent advancements in NLP led to a technique called LoRA, which aims to make fine-tuning more efficient by updating only low-rank parameters, but it suffers from significant approximation errors.
  • The proposed momentum imitation learning (MoIL) method improves upon LoRA by optimizing the approximation error and making the adaptation process more efficient, showing better performance in experiments across several vision-language tasks with minimal parameter updates.
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