This is a follow-up to previous work looking at which format of TABULAR data LLMs understand best:
https://www.improvingagents.com/blog/best-input-data-format-...(There was some good discussion on Hacker News around that here: https://news.ycombinator.com/item?id=45458455)
We often want to feed NON-TABULAR data to LLMs, though, such as typical API responses or config files.
This new work looks out how the format of such nested / hierarchical data affects how well LLMs can answer questions about it; specifically how several models get on with JSON, YAML, XML and Markdown.
