4 papers
Has My System Prompt Been Used? Large Language Model Prompt Membership Inference
Roman Levin, Valeriia Cherepanova, Abhimanyu Hans +2
Prompt engineering has emerged as a powerful technique for optimizing large language models (LLMs) for specific applications, enabling faster prototyping and improved performance,…
Transformers Boost the Performance of Decision Trees on Tabular Data across Sample Sizes
Mayuka Jayawardhana, Renbo, Samuel Dooley +6
Large language models (LLMs) perform remarkably well on tabular datasets in zero- and few-shot settings, since they can extract meaning from natural language column headers that de…
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
Benjamin Feuer, Robin Tibor Schirrmeister, Valeriia Cherepanova +5
While tabular classification has traditionally relied on from-scratch training, a recent breakthrough called prior-data fitted networks (PFNs) challenges this approach. Similar to…
Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text
Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova +5
Detecting text generated by modern large language models is thought to be hard, as both LLMs and humans can exhibit a wide range of complex behaviors. However, we find that a score…