From the 1 of 8 linked papers with an AI index.
8 papers
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…
Not All Code Is Equal: A Data-Centric Study of Code Complexity and LLM Reasoning
Lukas Twist, Shu Yang, Hanqi Yan +4
Large Language Models (LLMs) increasingly exhibit strong reasoning abilities, often attributed to their capacity to generate chain-of-thought-style intermediate reasoning. Recent w…
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…
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…
AI Agentic Programming: A Survey of Techniques, Challenges, and Opportunities
Huanting Wang, Jingzhi Gong, Huawei Zhang +2
The paper surveys the emerging field of AI agentic programming, where large language model‑based coding agents autonomously plan, execute, and interact with development tools, and…
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…