Author

Xingrui Yu

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#artificial intelligence Preprint Oct 2026

Judged Useless, Queried Anyway: Tool-Using Agents Rarely Turn Their Own Evidence Judgments into Stopping Decisions

An agent whose tool keeps returning nothing useful should stop relying on it. In a retrieval environment with controlled source failures, we separate how agents judge results from what they do. We compare stopping at the same step after longer and shorter runs of results the agent judged useless; this contrast is zero...

Chubin Zhang, Zheng-Lin Wan, Xing-Rui Yu et al. · 0 citations

#artificial intelligence Preprint Sep 2026

CUA-Sandbox: Efficient Environments for Computer-Use Agent Reinforcement Learning

CUA-Sandbox is introduced, which separates private state capsules from shared runtimes through state-scoped execution and transactional lifecycle operations, including resets and branches, while retaining the original software interfaces and task evaluators.

Xin Yan, Zheng-Bo Jiao, Jia-Qi Liu et al. · 0 citations

#artificial intelligence Preprint Aug 2026

SpikeOPD: Stable On-Policy Distillation for Autoregressive Spiking Language Models

Spiking neural networks (SNNs) offer a path to energy-efficient language modeling through sparse encoding and event-driven computation, but training capable spiking language models from scratch remains difficult. A practical alternative is ANN-to-SNN migration through knowledge distillation (KD), where a pretrained art...

En-Qiao Lu, Xingrui Yu, Yi-Wei Fu et al. · 0 citations