Large Language Models Struggle with Tabular Data
In brief
- Researchers found that large language models fail at predictive analytics over tabular data.
- This matters because large language models are widely used for many tasks.
- They are not good at handling data in tables.
- Tests on 31 datasets showed that large language models get less accurate as the data gets more complex.
- Large language models will likely keep improving, and may one day be good at handling tabular data.
Terms in this brief
- tabular data
- Data organized in rows and columns, like spreadsheets or databases. This format is common in many applications, such as tracking measurements or transactions, but it can be challenging for large language models to process effectively.
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