Context Window Optimization: Architectural Paradigms, Retrieval Integration, and the Mechanics of Million-Token Inference

1. Introduction: The Epoch of Infinite Context The trajectory of Large Language Model (LLM) development has undergone a seismic shift, moving from the parameter-scaling wars of the early 2020s to Read More …

Architectures of Scale: A Technical Report on Long-Context Windows in Transformer Models

Executive Summary The capacity of Large Language Models (LLMs) to process and reason over extensive sequences of information—a capability defined by their “context window”—has become a pivotal frontier in artificial Read More …

Architectures and Strategies for Scaling Language Models to 100K+ Token Contexts

The Quadratic Barrier: Fundamental Constraints in Transformer Scaling The transformative success of Large Language Models (LLMs) is built upon the Transformer architecture, a design that excels at capturing complex dependencies Read More …