Curating Same-Family Neural Networks for LLM-Guided Model Improvement: A Controlled Case Study

arXiv:2607.05704 · cs.LG, cs.CV · Submitted 2026-07-06 · Read on arXiv

cs.LG, cs.CV

Submitted: 2026-07-06

Updated: 2026-08-26

Terminology

• Accuracy — 47× in this paper · explained in 1 episode
• Adaptation — 8× in this paper · explained in 1 episode
• Robustness — 7× in this paper · explained in 5 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Action Space — 2× in this paper · explained in 1 episode
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Computer Vision and Pattern Recognition Workshops — 1× in this paper
• Iterative Refinement — 1× in this paper · explained in 3 episodes

Sources

• Evaluating Large Language Models Trained on Code
• LEMUR Neural Network Dataset: Towards Seamless AutoML
• Resource-Efficient Iterative LLM-Based NAS with Feedback Memory
• EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers
• LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimization
• AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
• Large Language Models as Optimizers
• Neural Architecture Search with Reinforcement Learning

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