Understanding LLM Performance Degradation in Multi-Instance Processing: The Roles of Instance Count and Context Length

ArXi:2603.22608v1 Announce Type: new Users often rely on Large Language Models (LLMs) for processing multiple documents or performing analysis over a number of instances. For example, analysing the overall sentiment of a number of movie reviews requires an LLM to process the sentiment of each review individually in order to provide a final aggregated answer. While LLM performance on such individual tasks is generally high, there has been little research on how LLMs perform when dealing with multi-instance inputs.