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Found 3 papers, 1 papers with code
IMPROVE: Iterative Model Pipeline Refinement and Optimization Leveraging LLM Agents
These findings establish Iterative Refinement as an effective new strategy for LLM-driven ML automation and position IMPROVE as an accessible solution for building high-quality computer vision models without requiring ML expertise.
Building a Mind Palace: Structuring Environment-Grounded Semantic Graphs for Effective Long Video Analysis with LLMs
Long-form video understanding with Large Vision Language Models is challenged by the need to analyze temporally dispersed yet spatially concentrated key moments within limited context windows.
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation
Pre-trained vision-language models (VLMs) have shown impressive results in various visual classification tasks.
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