4 papers
Assessing the Latent Automated Program Repair Capabilities of Large Language Models using Round-Trip Translation
Fernando Vallecillos Ruiz, Anastasiia Grishina, Max Hort +1
Research shows that errors in natural language can be corrected by translating texts to another language and back using language models. We explore to what extent this latent corre…
Towards deployment-centric multimodal AI beyond vision and language
Xianyuan Liu, Jiayang Zhang, Shuo Zhou +45
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as h…
The Impact of Fine-tuning Large Language Models on Automated Program Repair
Roman MacháÄek, Anastasiia Grishina, Max Hort +1
Automated Program Repair (APR) uses various tools and techniques to help developers achieve functional and error-free code faster. In recent years, Large Language Models (LLMs) hav…
Fully Autonomous Programming using Iterative Multi-Agent Debugging with Large Language Models
Anastasiia Grishina, Vadim Liventsev, Aki Härmä +1
Program synthesis with Large Language Models (LLMs) suffers from a "near-miss syndrome": the generated code closely resembles a correct solution but fails unit tests due to minor e…