Scholarlink

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.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Neural Network Verification is a Programming Language Challenge

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

查看全文
  • Lucas C. Cordeiro,
  • Matthew L. Daggitt,
  • Julien Girard-Satabin,
  • Omri Isac,
  • Taylor T. Johnson,
  • Guy Katz,
  • Ekaterina Komendantskaya,
  • Augustin Lemesle,
  • Edoardo Manino,
  • Artjoms Šinkarovs,
  • Haoze Wu

摘要

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.