Context Rot: How Increasing Input Tokens Impacts LLM Performance

When large language models (LLMs) hallucinate, developers typically assume the model lacks the required facts. Engineering teams diagnose the error as missing knowledge. The standard response is to increase model size, expand training data, or build complex retrieval architectures.A new study by res

Sep 1, 2026

Large language models (LLMs) like OpenAI’s GPT-4 are all the rage these days, owing to their unparalleled ability to analyze and generate text. But for organizations looking to leverage LLMs for specific tasks — say, writing ad copy in a brand’s style — their generalist nature can become a liability. When the instructions get too […]

Jun 27, 2023