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20212025
most citedLanguage Models for Code Optimization: Survey, Challenges and Future Directions

5 citations · 11 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SE2025

Evolving Excellence: Automated Optimization of LLM-based Agents

Paul Brookes, Vardan Voskanyan, Rafail Giavrimis +18

Agentic AI systems built on large language models (LLMs) offer significant potential for automating complex workflows, from software development to customer support. However, LLM a…

cs.SE2025

Industrial LLM-based Code Optimization under Regulation: A Mixture-of-Agents Approach

Mari Ashiga, Vardan Voskanyan, Fateme Dinmohammadi +7

Recent advancements in Large Language Models (LLMs) for code optimization have enabled industrial platforms to automate software performance engineering at unprecedented scale and…

cs.SE2025

Tuning LLM-based Code Optimization via Meta-Prompting: An Industrial Perspective

Jingzhi Gong, Rafail Giavrimis, Paul Brookes +8

There is a growing interest in leveraging multiple large language models (LLMs) for automated code optimization. However, industrial platforms deploying multiple LLMs face a critic…

cs.CL2025

Ensemble Learning for Large Language Models in Text and Code Generation: A Survey

Mari Ashiga, Wei Jie, Fan Wu +5

Generative Pretrained Transformers (GPTs) are foundational Large Language Models (LLMs) for text generation. However, individual LLMs often produce inconsistent outputs and exhibit…

cs.SE2025★ 5 cited

Language Models for Code Optimization: Survey, Challenges and Future Directions

Jingzhi Gong, Vardan Voskanyan, Paul Brookes +7

Language models (LMs) built upon deep neural networks (DNNs) have recently demonstrated breakthrough effectiveness in software engineering tasks such as code generation, completion…

cs.AI2022★ 1 cited

evoML Yellow Paper: Evolutionary AI and Optimisation Studio

Lingbo Li, Leslie Kanthan, Michail Basios +10

Machine learning model development and optimisation can be a rather cumbersome and resource-intensive process. Custom models are often more difficult to build and deploy, and they…

cs.SE2021★ 5 cited

Do Names Echo Semantics? A Large-Scale Study of Identifiers Used in C++'s Named Casts

Constantin Cezar Petrescu, Sam Smith, Rafail Giavrimis +1

Developers relax restrictions on a type to reuse methods with other types. While type casts are prevalent, in weakly typed languages such as C++, they are also extremely permissive…