Exploring Diagnostic Prompting Approach for Multimodal LLM-based Visual Complexity Assessment: A Case Study of Amazon Search Result Pages
Analysis
This research explores a novel approach to assess the visual complexity of web pages, specifically Amazon search results, using multimodal LLMs. The diagnostic prompting method is likely the core innovation, aiming to improve the accuracy and interpretability of complexity assessments. The focus on a real-world application (Amazon search results) adds practical relevance. The use of ArXiv as the source indicates this is a pre-print, suggesting the work is preliminary and hasn't undergone peer review.
Key Takeaways
“The research likely investigates how different prompting strategies influence the LLM's ability to analyze and quantify visual complexity. The case study on Amazon search results provides a concrete context for evaluating the effectiveness of the proposed approach.”