43 citations · 73 across the 9 of their papers we have counts for
9 papers
The Impact of Fine-tuning Large Language Models on Automated Program Repair
Roman Macháček, 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…
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…
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…
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…
An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code
Max Hort, Anastasiia Grishina, Leon Moonen
Large language models trained on source code can support a variety of software development tasks, such as code recommendation and program repair. Large amounts of data for training…
The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification
Anastasiia Grishina, Max Hort, Leon Moonen
The use of modern Natural Language Processing (NLP) techniques has shown to be beneficial for software engineering tasks, such as vulnerability detection and type inference. Howeve…
Fully Autonomous Programming with Large Language Models
Vadim Liventsev, Anastasiia Grishina, Aki Härmä +1
Current approaches to program synthesis with Large Language Models (LLMs) exhibit a "near miss syndrome": they tend to generate programs that semantically resemble the correct answ…
Enabling Automatic Repair of Source Code Vulnerabilities Using Data-Driven Methods
Anastasiia Grishina
Users around the world rely on software-intensive systems in their day-to-day activities. These systems regularly contain bugs and security vulnerabilities. To facilitate bug fixin…
Towards More Reliable Automated Program Repair by Integrating Static Analysis Techniques
Omar I. Al-Bataineh, Anastasiia Grishina, Leon Moonen
A long-standing open challenge for automated program repair is the overfitting problem, which is caused by having insufficient or incomplete specifications to validate whether a ge…