Author

Huan-Jin Yao

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#artificial intelligence Preprint Sep 2026

AutoDataBench: Can Agents Write the Data That Feeds the Self-Improvement Loop?

Recent gains in language model capability have come more from data than from architecture. Frontier labs and data companies produce verifiable agentic tasks, which supervised finetuning and reinforcement learning then turn into capability.This production line still rests on human labour and on human-in-the-loop collabo...

Haotian Luo, Hao-Yu Wang, Ze-Yu Qin et al. · 0 citations

Jul 2026

SceneActBench: Can Agents Act on the 3D Scenes They See?

This work presents SceneActBench, a benchmark for visually conditioned action across five 3D tasks under a unified agent-environment loop, and evaluates each final output against hidden ground truth with task-specific geometric metrics.

Yifei Zhao, Xiangxin Zhou, Wenhao Yang et al. · arXiv.org · 2 citations