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Keyword: membership inference attacks ×Clear all

1 claim from 1 paper

1. Computer Science › Topic Modeling

   Task Contamination: Language Models May Not Be Few-Shot Anymore

   Li and Flanigan · arXiv (Cornell University) · 2023

   The paper examines whether zero-shot and few-shot results of large language models are inflated by task contamination, tracking performance over time and using several methods to look for evidence of it.

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   1. UncheckedIn this study, language models did surprisingly better on datasets released before their training data was created than on later ones, after controlling for difficulty.“Utilizing GPT-3 series models and several other recent open-sourced LLMs, and controlling for dataset difficulty, we find that on datasets released before the LLM training data creation date, LLMs perform surprisingly better than on datasets released after.”