Summary of The Fifth International Verification Of Neural Networks Competition (vnn-comp 2024): Summary and Results, by Christopher Brix et al.
The Fifth International Verification of Neural Networks Competition (VNN-COMP 2024): Summary and Results
by Christopher Brix, Stanley Bak, Taylor T. Johnson, Haoze Wu
First submitted to arxiv on: 28 Dec 2024
Categories
- Main: Machine Learning (cs.LG)
- 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 5th International Verification of Neural Networks Competition (VNN-COMP 2024) is an annual event that brings together the neural network verification community to compare state-of-the-art verification tools. The competition evaluates neural networks on standardized benchmarks, using a fair and objective evaluation pipeline based on AWS instances. Eight teams participated in the 2024 iteration, testing their tools on 12 regular and 8 extended benchmarks. This report summarizes the rules, participating tools, results, and lessons learned from this iteration of VNN-COMP. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The VNN-COMP competition is an important event that helps to advance the field of neural network verification. By comparing different tools and techniques, researchers can identify what works best for specific tasks and applications. This year’s competition included a diverse range of benchmarks, which allowed teams to test their tools in different scenarios. |
Keywords
» Artificial intelligence » Neural network
