Long Input Scroll Benchmark

Long input scroll benchmarks evaluate the ability of large language models (LLMs) to process and understand extremely long text sequences, exceeding the capabilities of traditional benchmarks. Current research focuses on developing benchmarks with varying lengths (up to 128k tokens) and diverse tasks, including question answering and summarization, to rigorously assess LLMs across different length ranges and model architectures, such as transformers with conditional computation. These benchmarks are crucial for advancing LLM development by identifying limitations in long-context understanding and driving improvements in efficiency and performance for applications requiring the processing of extensive textual data.