Resolving Evidence Sparsity: Agentic Context Engineering for Long-Document Understanding

This article, sourced from ArXiv, focuses on a research area within the field of Large Language Models (LLMs). The title suggests a technical approach to improve LLMs' ability to process and understand long documents, specifically addressing the challenge of evidence sparsity. The use of "Agentic Context Engineering" indicates a novel method, likely involving the use of agents to strategically manage and extract relevant information from lengthy texts. The research likely aims to enhance the performance of LLMs in tasks requiring comprehensive understanding of extensive documents.