Evaluating Abstractive Summarization - Part 2
Limitations
Note that LLM-based metrics could have a bias towards preferring LLM-generated texts over human-written texts. Additionally LLM based metrics are sensitive to system messages/prompts. We recommend experimenting with other techniques that can help improve performance and/or get consistent scores, striking the right balance between high-quality expensive evaluation and automated evaluations. It is also worth noting that this scoring methodology is currently limited by gpt-4's context window.