将神经网络验证转化为编程语言问题，推动算法革新。
Neural Network Verification is a Programming Language Challenge
- 从编程语言视角重构神经网络验证难题
- 提出可提升验证效率的新方法框架
- 适合关注形式化验证与系统安全的研究者
神经网络验证是一个快速发展的研究领域。迄今为止，主要工作集中在开发高效的验证算法与工具，而编程语言层面的支持则被视为次要或无关紧要。然而，越来越多的证据表明，来自编程语言领域的洞见可能在未来对该领域的发展产生重要影响。本文将神经网络验证挑战重新定义为编程语言挑战，并提出未来可能的解决方案。
原文摘要 · Abstract (English)
Neural network verification is a new and rapidly developing field of research. So far, the main priority has been establishing efficient verification algorithms and tools, while proper support from the programming language perspective has been considered secondary or unimportant. Yet, there is mounting evidence that insights from the programming language community may make a difference in the future development of this domain. In this paper, we formulate neural network verification challenges as programming language challenges and suggest possible future solutions.
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