23 citations · 23 across the 7 of their papers we have counts for
4 papers · 1 filter
Recursive self-improvement of AI research agents
Dhruv Srikanth, Bingchen Zhao, Dixing Xu +2
AI agents are beginning to automate research and development across the AI stack, from improving training efficiency to optimizing inference. A natural next step is to improve the…
AutoData: Agentic Search for Pre-training Data Selection
Yan Meng, Dhruv Srikanth, Bingchen Zhao +2
LLM agents have recently shown promise in automating machine learning engineering by editing model and training code under execution feedback. Data, however, remains largely outsid…
Hyperagents
Jenny Zhang, Bingchen Zhao, Wannan Yang +5
Self-improving AI systems aim to reduce reliance on human engineering by learning to improve their own learning and problem-solving processes. Existing approaches to self-improveme…
The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements
Bingchen Zhao, Despoina Magka, Minqi Jiang +20
Rapid advancements in large language models (LLMs) have the potential to assist in scientific progress. A critical capability toward this endeavor is the ability to reproduce exist…