7 citations · 25 across the 12 of their papers we have counts for
14 papers
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…
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…
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…
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…
Weak-strong uniqueness for solutions to mean-field games
Rita Ferreira, Diogo Gomes, Vardan Voskanyan
This paper addresses the crucial question of solution uniqueness in stationary first-order Mean-Field Games (MFGs). Despite well-established existence results, establishing uniquen…
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…
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…
Sharp regularity for singular obstacle problems
Damião J. Araújo, Rafayel Teymurazyan, Vardan Voskanyan
We obtain sharp local regularity of solutions for singular obstacle problems, Euler-Lagrange equation of which is given by …
On a Mean Field Optimal Control Problem
Jose A. Carrillo, Edgard A. Pimentel, Vardan K. Voskanyan
In this paper we consider a mean field optimal control problem with an aggregation-diffusion constraint, where agents interact through a potential, in the presence of a Gaussian no…
Existence of positive solutions for an approximation of stationary mean-field games
Nojood Almayouf, Elena Bachini, Andreia Chapouto +22
Here, we consider a regularized mean-field game model that features a low-order regularization. We prove the existence of solutions with positive density. To do so, we combine a pr…
Regularity for second order stationary mean-field games
Edgard A. Pimentel, Vardan Voskanyan
In this paper, we prove the existence of classical solutions for second order stationary mean-field game systems. These arise in ergodic (mean-field) optimal control, convex degene…
Short-time existence of solutions for mean-field games with congestion
Diogo Gomes, Vardan Voskanyan
We consider time-dependent mean-field games with congestion that are given by a system of a Hamilton-Jacobi equation coupled with a Fokker-Planck equation. The congestion effects m…
On the existence of classical solutions for stationary extended mean field games
Diogo A. Gomes, Stefania Patrizi, Vardan Voskanyan
In this paper we consider extended stationary mean field games, that is mean-field games which depend on the velocity field of the players. We prove various a-priori estimates whic…
Extended deterministic mean-field games
Diogo A. Gomes, Vardan K. Voskanyan
In this paper, we consider mean-field games where the interaction of each player with the mean-field takes into account not only the states of the players but also their collective…