Code Detection

Code detection research focuses on reliably identifying instances of code within various contexts, addressing challenges like copyright infringement in large language models (LLMs) and fraudulent activities in blockchain. Current approaches leverage both code-based methods (analyzing syntax and semantics) and transaction-based methods (examining blockchain activity), with recent work exploring the use of LLMs themselves for improved accuracy and robustness. These advancements have significant implications for software auditing, intellectual property protection, and the detection of malicious code in decentralized systems.