Lost in the Middle: Language Model Long Context Evaluation
What it is
A research repository providing code and data to evaluate how Large Language Models (LLMs) process long contexts. It includes experiments and datasets for multi-document question answering and key-value retrieval.
The problem it solves
LLMs often exhibit degraded performance when processing long contexts, particularly when relevant information is buried in the middle of the input.
What you could use it for
- Evaluating LLM performance on long-context retrieval tasks
- Generating synthetic multi-document QA data for testing
- Benchmarking key-value retrieval accuracy in long contexts
- Testing the impact of information position on model response quality
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.