4 papers
Sakana Fugu Technical Report
Yujin Tang, Edoardo Cetin, Jinglue Xu +11
The capabilities of frontier Large Language Models (LLMs) continue to advance, with different providers increasingly specializing in distinct domains. This raises a natural next ob…
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…
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…
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…