Asymmetric Capacity Allocation in Self-Refinement Pipelines
探索自精炼流程中非对称容量分配策略,揭秘资源优化与推理效率的关键突破。
arXiv:2608.21345v1 Announce Type: new Abstract: Self-refinement, typically structured as generation, critique, and revision, is a widely adopted parad…
探索自精炼流程中非对称容量分配策略,揭秘资源优化与推理效率的关键突破。
arXiv:2608.21345v1 Announce Type: new Abstract: Self-refinement, typically structured as generation, critique, and revision, is a widely adopted parad…
评估LLM代理在预算约束下的经济决策,揭示资源效率与任务完成度的平衡新基准。
arXiv:2608.05519v1 Announce Type: new Abstract: Agent benchmarks usually measure task completion and treat resource use as an auxiliary statistic. In …
Java 24新特性遇上K8s 1.33平台工程,解锁企业级AI资源调度与GPU精细化管理新姿势。
Beyond the Hype: Mastering Java 24 Patterns and K8s 1.33 for Enterprise AI Ops As we move into March 2026, the intersection of Java 24 , Kubernetes 1.…
解耦LLM后训练中的GPU资源瓶颈,用强化学习实现运行时动态分配,大幅提升算力利用率。
arXiv:2607.22614v2 Announce Type: replace Abstract: RL-based LLM post-training increasingly disaggregates Rollout and Training across separate GPU res…
从微小公司管理者视角,犀利质疑AI生产力缺乏整体性数据,直击成本效益决策痛点。
Article URL: https://rachelandrew.co.uk/archives/2026/06/11/wheres-the-holistic-ai-productivity-data/ Comments URL: https://news.ycombinator.com/item?…
单GPU实现凸优化方法,高效解决LLM偏好对齐难题,降低RLHF计算成本。
arXiv:2605.23244v1 Announce Type: new Abstract: Fine-tuning large language models (LLMs) to align with human preferences has driven the success of sys…
docs.rs 默认构建目标从五个减为一个,2026年5月起生效,节省资源并加速构建,多目标 crate 需手动配置。
Building fewer targets by default On 2026-05-01 , docs.rs will make a breaking change to its build behavior. Today, if a crate does not define a targe…