LLMTabBench evaluates LLMs on zero- and few-shot binary tabular classification and reports that zero-shot can outperform few-shot due to example conflicts with model priors while performance drops beyond a complexity threshold.
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LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots
LLMTabBench evaluates LLMs on zero- and few-shot binary tabular classification and reports that zero-shot can outperform few-shot due to example conflicts with model priors while performance drops beyond a complexity threshold.