Summary of Models That Prove Their Own Correctness, by Noga Amit et al.
Models That Prove Their Own Correctness
by Noga Amit, Shafi Goldwasser, Orr Paradise, Guy Rothblum
First submitted to arxiv on: 24 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computational Complexity (cs.CC); Software Engineering (cs.SE)
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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 This paper proposes a solution to ensure the correctness of a learned model’s output on a specific input, which is typically not guaranteed by average accuracy measurements. The approach involves training “Self-Proving models” that prove their output is correct through an Interactive Proof with a verification algorithm V. These models satisfy that they generate correct outputs and successfully prove their correctness to V most of the time. The soundness property of V ensures that no model can convince V of an incorrect output for any input, effectively detecting all incorrect outputs. A generic method for learning Self-Proving models is devised, along with convergence bounds under certain assumptions. Experiments on computing the greatest common divisor (GCD) of two integers using a transformer demonstrate the effectiveness of this approach. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper tries to solve a problem where we want to make sure a model’s answer is correct for a specific question. Right now, we can only check how well a model does on average, not for one specific question. The idea is to create “Self-Proving models” that not only give the right answer but also explain why it’s correct. This way, we can trust that most of the time the model gives the correct answer and catch when it makes a mistake. To do this, the paper proposes a special kind of proof called an Interactive Proof that works with a special algorithm V. The goal is to make sure that no matter what question you ask, the model’s answer will be correct and V will agree. |
Keywords
» Artificial intelligence » Transformer
