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Quantitative Finance · Begrippenlijst

Wat is Memorisation, anonymisation test?

Ook bekend als: memorisation · anonymisation test

Definition 14.5 Machine Learning for Markets · Hoofdstuk 14 — Large Language Models in Finance

Memorisation is a model’s ability to reproduce specific training examples, including their outcomes, rather than a rule that generalises; language models memorise text seen even once (Carlini and co-authors, 2021). The anonymisation test replaces the identifiers in an input (company names, tickers, dates) by placeholders and measures how much the model’s accuracy falls: a model that reads the text loses little, a model that recalls the event loses its memory.

Share of headlines whose direction each model predicts correctly, by period, with names and weeks and with placeholders. The clean model’s training data end at the first cut-off, the contaminated model’s at the second. Dashed: the sign of the planted effect. Data: ml_llm.contamination.
Figure 14.2. Share of headlines whose direction each model predicts correctly, by period, with names and weeks and with placeholders. The clean model’s training data end at the first cut-off, the contaminated model’s at the second. Dashed: the sign of the planted effect. Data: ml_llm.contamination.
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