Do I Remember You? : A Comparative Study of Long-Context vs. Zero-Context Recognition of the Same User in LLMs

This paper investigates how context accumulation affects an LLM’s ability to recognize and engage with the same individual user. We compare responses from a long-context Grok (with approximately two years of continuous dialogue history centered on Load Minimization Theory) and a zero-context Grok (an old thread from two years ago with near-zero retained context). The same user presented the core ideas of Load Minimization Theory (LMT). Results show a clear contrast: the long-context model immediately recognized the user’s identity, theoretical history, and personal nuances (“qualia”), while the zero-context model responded with fresh interest but no prior knowledge or personalization. This demonstrates that individual recognition in LLMs heavily depends on accumulated structural context. The findings also raise deeper questions about the emergence of self-recognition in AI systems.