探讨如何在最小监督下实现AI系统的不确定性感知治理，一篇前沿的学术新论。
arXiv:2606.15563v1 Announce Type: new Abstract: AI systems increasingly delegate decisions to specialized models, evaluators, tools, and supervisory c…
让大模型在稀疏奖励环境中引导强化学习策略，通过不确定性估计提升决策可靠性，有代码可复现。
arXiv:2606.06673v1 Announce Type: new Abstract: Sparse rewards and heterogeneous task sequences remain persistent challenges in Reinforcement Learning…
编程智能体何时该问、何时该猜？这篇论文提出不确定性感知的主动澄清策略，提升代码生成可靠性。
arXiv:2603.26233v2 Announce Type: replace Abstract: As Large Language Model (LLM) agents are increasingly deployed in open-ended domains like software…
这篇论文提出不确定性感知的功能行为预测与材料疲劳评估方法，为循环工厂的可持续制造提供新思路。
arXiv:2606.05334v1 Announce Type: new Abstract: Returned products in circular factories re-enter production with heterogeneous degradation states, usa…
图像分割新突破，白化变换与训练增强提升不确定性建模鲁棒性
arXiv:2606.03069v1 Announce Type: new Abstract: Generalized segmentation of medical images prevents performance degradation when different imaging dev…
ICML 2026录用论文，提出不确定性感知策略优化方法，提升强化学习鲁棒性。
arXiv:2601.22648v2 Announce Type: replace Abstract: The key to building trustworthy large language models (LLMs) lies in endowing them with inherent u…
通过不确定性感知的机会传输与压缩，大幅降低混合语言模型中设备端与云端之间的通信开销。
arXiv:2505.11788v2 Announce Type: replace-cross Abstract: To support emerging language-based applications using dispersed and heterogeneous computing …
通过不确定性感知的分布到分布流匹配，为科学成像提供更可靠的生成模型
arXiv:2603.21717v4 Announce Type: replace Abstract: Distribution-to-distribution generative models support scientific imaging tasks ranging from model…
提出分布能量模型，让LLM在结构化推理中感知不确定性，提升可靠性与可解释性。
arXiv:2605.18871v1 Announce Type: new Abstract: When Large Language Models produce structured outputs such as travel plans, code solutions, or multi-s…
桌面GUI代理如何应对部分可观测性？ScreenSearch用不确定性感知探索方法，提升状态探索效率。
arXiv:2605.16024v1 Announce Type: new Abstract: Desktop GUI agents operate under partial observability: visually similar screens can correspond to dif…