Summary of The 20 Questions Game to Distinguish Large Language Models, by Gurvan Richardeau et al.
The 20 questions game to distinguish large language models
by Gurvan Richardeau, Erwan Le Merrer, Camilla Penzo, Gilles Tredan
First submitted to arxiv on: 16 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents a method to determine whether two large language models (LLMs) are the same or not, by asking a small set of binary questions. The goal is to achieve high accuracy with minimal questions. A baseline is established using random selection from known benchmark datasets, achieving nearly 100% accuracy within 20 questions. Two questioning heuristics are introduced, able to discriminate between 22 LLMs using half the number of questions required for the same task. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps figure out if two big language models are identical or not by asking a few simple yes-or-no questions. It’s like playing 20 questions! The researchers tried different methods and found that they could tell apart many language models with just a few questions. This is useful for people who want to make sure no one is copying their work without permission. |
