Author

Rushi Qiang

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Preprint Sep 2026

RLE-Bench: A Qualifying Exam for Coding Agents as Robot Learning Engineers

Coding agents are beginning to move beyond purely digital tasks to tackle physical-world challenges, particularly in robotics. Existing robotics benchmarks, however, primarily focus on the performance of individual artifacts, such as policies or controllers, offering limited coverage of coding agents'broader engineerin...

Hai-Tong Ma, Chen-Xiao Gao, Ru-Shi Qiang et al. · 0 citations

Jul 2026

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

Recursive self-improvement (RSI) requires AI systems that improve the process of building AI (i.e., AI4AI); machine learning engineering (MLE) offers a concrete, executable testbed for studying this capability. We introduce OpenMLE, an open full-stack system for RSI research in MLE, spanning verifiable task environment...

Junlin Yang, Che Jiang, Yu Fu et al. · arXiv.org · 3 citations

Jul 2026

Matryoshka Agent: Unfolding Sub-Agents for Long-Horizon Machine Learning Engineering

Experimental results on a broad range of MLE tasks with diverse model types and scales demonstrate that Matryoshka Agent is an effective and scalable paradigm for long-horizon MLE tasks and complex agentic problem solving.

Rushi Qiang, Changhao Li, Haotian Sun et al. · arXiv.org · 0 citations