Real World Code
Real-world code research focuses on bridging the gap between large language models (LLMs) and practical software development, aiming to improve the quality, security, and efficiency of automatically generated code. Current research emphasizes developing methods for generating equivalent code representations, ensuring code correctness through techniques like hierarchical debugging and polyhedral modeling, and mitigating security vulnerabilities via prompt optimization and generative adversarial networks. This field is significant because it directly impacts software engineering practices, potentially increasing developer productivity and improving software reliability and security.
Papers
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Viraat Aryabumi, Yixuan Su, Raymond Ma, Adrien Morisot, Ivan Zhang, Acyr Locatelli, Marzieh Fadaee, Ahmet Üstün, Sara Hooker
ProgramAlly: Creating Custom Visual Access Programs via Multi-Modal End-User Programming
Jaylin Herskovitz, Andi Xu, Rahaf Alharbi, Anhong Guo