Inputs were not long enough to properly see either of the true wins in terms of reduced token counts for terser formats or their benefits in terms of avoiding stuffing the context window thereby potentially reducing accuracy. The test really needs to be conducted across multiple dimensions!
Which table format do LLMs understand best?
21–30 of 115 posts
Re: Which table format do LLMs understand best?
#22KSON? (I'm a complete ignoramus in this area but recently read about KSON in a piece posted here at HN.)
https://ochagavia.nl/blog/configuration-files-are-user-inter...
https://news.ycombinator.com/item?id=45291858 (135 comments)
Re: Which table format do LLMs understand best?
#23Tbh I am more interested in processing data and formatting it to tabular forms than extracting data from tabular forms. One of the main uses I see in LLMs is structuring unstructured/semistructured data. I may occasionally feed a table to an LLM and ask such kinds of questions when I feel lazy, but I see no serious application of this as compared with using whatever language/library to process the data from the table (whether using an llm or not in the whole process). The point of having structured data is exactly this. But much more often I feed data to an llm and ask it to create a table.
Re: Which table format do LLMs understand best?
#24Bizarre conclusions when on average all the formats perform poorly with average accuracy of 50%. Sure 60% is better than 40% but they are both unusable if you actually care about numbers...
My sentiments exactly. All the formats were so poorly read that they are all effectively useless.
Re: Which table format do LLMs understand best?
#25> where accuracy is paramount > accuracy: 60% Not to mention that the least poorly performing format is probably the stupidest way to encode tabular data, beating even XML. But I guess that’s the new normal because we’re trying to shoehorn conversational AI models to every use case rather than, say, training finetunes that are better at particular tasks. (Yes, of course you can’t train finetunes when the model is a p…
they used GPT-4.1 nano, results would be quite different with sonnet or gpt5.
Or just regular gpt-4.1, it's a quite capable model.
Re: Which table format do LLMs understand best?
#26I'm surprised by the accuracy, in practice, I feel like I generally have a lot better results
Re: Which table format do LLMs understand best?
#27I'm surprised by the accuracy, in practice, I feel like I generally have a lot better results
Do you measure your results in a repeatable way? In a way where your hypotheses about accuracy are falsifiable? Or do they just “feel” right?
Re: Which table format do LLMs understand best?
#28I wonder how this compares to a more agentic approach where the LLM composes SQL queries to answer the questions, for example.
This was exactly my thought. Rather than feed the table directly to the LLM, build agents that extract the data and have the LLM act on the extracted data items. Then it’s a preference issue. The author didn’t see much more than 60% accuracy which is not very useful for many (most?) real world tasks.
“Agents that extract the data”
Are we really reinventing data frame readers to have an LLM in the critical path?
Re: Which table format do LLMs understand best?
#29Bizarre conclusions when on average all the formats perform poorly with average accuracy of 50%. Sure 60% is better than 40% but they are both unusable if you actually care about numbers...
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Re: Which table format do LLMs understand best?
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