利用赌博机制实现去中心化 LLM 预测聚合，无需公开模型私有信息即可提升集体预测性能
arXiv:2607.04389v1 Announce Type: new Abstract: It is increasingly common to aggregate predictions from multiple LLMs, each with domain expertise or a…
利用相似性结构提升多臂赌博机算法效率，最新arXiv论文探索更优的探索-利用权衡策略。
arXiv:2606.23414v1 Announce Type: new Abstract: In many online learning and bandit problems, the actions we consider possess inherent similarities--fo…
挑战在线LLM选择中的时变需求？这篇论文提出约束赌博机框架，动态平衡性能与成本。
arXiv:2606.17489v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in edge-cloud inference systems to handle div…
为大模型应用场景选择提供诊断工具，探究语言驱动赌博机何时需要LLM。
arXiv:2604.05859v2 Announce Type: replace Abstract: We study Contextual Multi-Armed Bandits (CMABs) for non-episodic decision-making problems where th…
探究核赌博机问题的算法与极小极大复杂度，理论机器学习新进展
arXiv:2606.11171v1 Announce Type: new Abstract: Gaussian-process upper confidence bound (GP-UCB) and decision-estimation-coefficient (DEC) methods may…
提出一种扰动方法，解决无约束线性赌博机的遗憾下界与最优算法设计问题，ICML 2026收录。
arXiv:2603.28201v2 Announce Type: replace Abstract: We revisit the standard perturbation-based approach of Abernethy et al. (2008) in the context of u…
离线数据下的风险感知策略学习新框架，用悲观原则优化高风险场景的决策效果
arXiv:2605.15620v1 Announce Type: cross Abstract: We study risk-aware offline policy learning, aiming to learn a decision rule from logged data that i…
用Markdown文件驱动多模型AI代理协作，实现任务路由与自我优化，让团队越用越强
Article URL: https://github.com/yehudalevy-collab/polis-protocol Comments URL: https://news.ycombinator.com/item?id=48171752 Points: 2 # Comments: 0