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The first thing I'd do if working with an LLM on tabular data is to ask what the best tool would be to work with that data and build up a proper harness to work
by _joel 2mo ago
The first thing I'd do if working with an LLM on tabular data is to ask what the best tool would be to work with that data and build up a proper harness to work with the data sensibly. Rawdogging LLM isn't the tool for forecasting like this, as they found.
- efromvt 2mo agoIt’s an interesting question of ‘why not’, though - this was a good read and is upstream of more practical output optimization.
- deleted 2mo ago[deleted]
- antonvs 2mo ago> Rawdogging LLM isn't the tool for forecasting like this, as they found. You seem to have misunderstood the paper. They didn’t find that LLMs weren’t the tool for this, that was essentially assumed as a well-known premise. The paper investigates why, specifically, that might be the case, by evaluating 5 hypotheses. What they found was a connection to dimensionality.