analiza aiqbench

This research introduces Context Language Models (CLMs), a novel architecture where large language models autonomously manage and edit their own context windows rather than relying on external summarization or retrieval mechanisms. By treating context as an editable file, CLMs demonstrate significant improvements in performance and computational efficiency while learning strategies that surpass traditional human-designed constraints. This advancement represents a fundamental shift toward intrinsic model behaviors for handling long-context tasks, directly addressing key challenges in scaling LLMs.