How to Apply Vision Language Models to Long Documents

Vision Language Models (VLMs) can be applied to long and dense documents for complex understanding tasks, offering an advantage over traditional OCR by interpreting visual context. One method involves using VLMs for advanced OCR to generate structured text like Markdown or to describe visual elements, which improves the performance of downstream LLMs. Another approach is to process document images directly, which requires balancing processing power, latency, and image resolution. The content also discusses the trade-offs between open-source and closed-source models for these tasks and suggests strategies like answer-dependent processing to manage computational costs.