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Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 07:36

Image Complexity-Aware Adaptive Retrieval for Efficient Vision-Language Models

Published:Dec 17, 2025 12:19
1 min read
ArXiv

Analysis

This article introduces a method for improving the efficiency of Vision-Language Models (VLMs) by adapting the retrieval process based on the complexity of the input image. This is a common approach in research, focusing on optimizing resource usage. The use of 'complexity-aware' suggests a nuanced approach to resource allocation.
Reference

Research#VLM🔬 ResearchAnalyzed: Jan 10, 2026 11:23

Adaptive Token Pruning Improves Vision-Language Reasoning Efficiency

Published:Dec 14, 2025 14:11
1 min read
ArXiv

Analysis

This ArXiv paper explores a method to enhance the efficiency of vision-language models. The focus on adaptive token pruning suggests a potential for significant performance gains in resource-constrained environments.
Reference

The article is based on a paper submitted to ArXiv.