"MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering" benchmarks AI agents on 75 Kaggle competitions. The best tested setup earned medals in 16.9% of contests. #MLE #AIAgents #AutoML buff.ly/PVMl4lz

The ALFIE AutoML Engine brings together:

🔹 Automated classification for text, audio & images
🔹 Data quality checks & bias detection
🔹 Explainable AI (XAI)
🔹 Ethical and responsible AI
🔹 An AI-powered assistant to guide users

#AutoML #ResponsibleAI #AI

This paper introduces Generative Adversarial Loops (GAL), a framework that pairs an adversarial data-creating agent with an algorithm-discovering agent so systems can challenge and improve themselves with less human input.

#GAL #AIResearch #AutoML #AgenticAI
https://arxiv.org/abs/2610.11458

DAGO treats workflow fusion as a bandit problem: learn which parent combos yield strong children under a fixed eval budget. +1.4 macro-avg, 11.2% less search spend. #AI #LLM #AutoML #Bandits

https://freegardner.com/synapse/dago-learns-which-workflows-to-fuse.html

EvoCast is a fully autonomous research-agent system for iterating on deep time-series forecasting architectures, using executed mechanism ablations and a cognition-authority separation to guide evidence-based design choices.

#AI #AutoML #TimeSeries #ArXiv
https://arxiv.org/abs/2610.04517

RankEvolve introduces an auto-research framework for evolving generative ranking models, using an Executable Operating Protocol to enforce a compiled state machine and a meta-meta-harness that composes agents like…

#AIResearch #AutoML #LLMAgents #RankingModels
https://arxiv.org/abs/2609.39551

Qmes uses meta-learning to automatically recommend quantum kernel encoding circuits without expensive per-dataset evaluation. Reduces mean regret by 2.2–4.2× versus baselines while eliminating quantum computation costs at inference time.

#QuantumML #AutoML #Research