Author

Ying Yuan

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Preprint Aug 2026

RAISE: Diagnosing Acquisition Collapse in Costly LLM Signals

Large language models (LLMs) are increasingly used as costly, on-demand components in real systems, but calling them indiscriminately can waste substantial compute, latency, and serving budget. The key deployment question is therefore not only whether an LLM helps on average, but when it is worth calling. We identify a...

Ying Yuan, Yu Wang, Yize Cheng et al. · 0 citations

#machine learning Preprint Aug 2026

Detecting an Effect Is Not Learning to Act on It: A Reward-SNR Floor for LLM Acquisition Agents

This thesis is a distinction that is easy to miss: detecting that such a signal helps on average is not the same as learning to act on it per instance, and a reward-SNR floor governs when the second is even possible, and a reward-SNR detectability floor is explained.

Ying Yuan · 0 citations

Jun 2026

From Grasps to Dexterity: Large-Scale Grasp Pretraining for Dexterous Manipulation

This work adapts a hierarchical imitation learning framework that combines high-level hand sub-goal prediction with a low-level goal-conditioned controller to serve not only as resources for grasp synthesis, but also as scalable pretraining data for contact-rich dexterous manipulation.

Ying Yuan, Xinyu Liu, Sriram Krishna et al. · arXiv.org · 0 citations