Optimizing Vision-Language Model Inference with Input-Adaptive Preprocessing
Published:Dec 23, 2025 23:30
•1 min read
•ArXiv
Analysis
This research paper explores a method for optimizing the inference of Vision-Language Models (VLMs), focusing on input-adaptive visual preprocessing. The proposed approach likely aims to improve efficiency by tailoring the preprocessing steps to the specific input data.
Key Takeaways
Reference
“The paper focuses on input-adaptive visual preprocessing for efficient VLM inference.”