5 citations · 13 across the 5 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.LG2026
Can LLMs predict the outcomes of machine learning experiments?
Ayush Bansal, Aldo Pareja, Sean Klein +2
Recent advances in AI make Recursive Self-Improvement (RSI) increasingly plausible. Large Language Models (LLMs) can already propose, select, and run Machine Learning (ML) experime…
cs.LG2026
BOAD: Discovering Hierarchical Software Engineering Agents via Bandit Optimization
Iris Xu, Guangtao Zeng, Zexue He +5
Large language models (LLMs) have shown strong reasoning and coding capabilities, yet they struggle to generalize to real-world software engineering (SWE) problems that are long-ho…