AssertLLM is a novel framework that leverages the power of multiple large language models (LLMs) to automate the generation of SystemVerilog Assertions (SVAs) from complex hardware design specifications, improving the efficiency and effectiveness of hardware verification.
AI 統合システム、特に学習分析におけるAIシステムの監査可能性を確保するためには、設計段階から監査可能性を考慮したフレームワークが必要である。
This research paper proposes JFuzz, a novel approach that integrates Large Language Models (LLMs) into JSON parser fuzzing to enhance bug discovery and analyze behavioral diversities among different parser implementations.