Papers

Filtered to machine learning engineering · clear filter

Browse by term

continual learning 91reinforcement learning 43vision-language models 18benchmarking 12benchmarks 11robotics 11large language models 10language models 9world models 9video generation 6generative models 5multimodal models 5natural language processing 5recursive self-improvement 5video world models 5agents 4dialogue systems 4diffusion models 4foundation models 4multimodal large language models 4on-policy distillation 4reasoning 4self-distillation 4self-supervised learning 4conversational AI 3evaluation benchmarks 3human-computer interaction 3LLMs 3multi-agent systems 3policy optimization 3

Matching papers

Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering

168 upvotes · 30 JUL 2026 · Junlin Yang, Che Jiang, Yu Fu et al.

This paper trains an AI model to improve itself in the process of building AI, with a focus on machine learning engineering, and shows promising results in various benchmarks. Practitioners may care about this research as it could lead to more efficient and autonomous AI development.