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
OpenMLE is introduced, an open full-stack system for RSI research in MLE, spanning verifiable task environments with execution feedback, operator learning, and long-horizon search (OpenMLE-Evo) and enabling reproducible research on executable AI4AI toward RSI.
Junlin Yang, Che Jiang, Yu Fu et al.· arXiv.org· 7 citations
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
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