Papers by Lucas Hurley McCabe

1 papers
Demystifying optimized prompts in language models (2025.emnlp-main)

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Challenge: Modern language models (LMs) are not robust to out-of-distribution inputs.
Approach: They investigate the composition of machine generated (“optimized”) prompts and the mechanisms by which LMs parse and build predictions from them.
Outcome: The proposed prompts are primarily composed of punctuation and noun tokens, which are more rare in the training data.

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