洞察 AI 演进与全球贸易脉动，以全息视野重塑跨域情报流。
Decoding AI evolution and global trade rhythms. High-fidelity intelligence, redefined.
China's EV makers shift gears to focus on humanoids as car market slows
中国公司十年前就涌入电动汽车,，现在随着电动汽车市场在激烈的竞争中出现放缓，他们正在扩展到人形机器人。
Chinese companies rushed into electric cars a decade ago, and now they are expanding into humanoid robots as the EV market sees a slowdown amid intens...
Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails
代理利用(系统提示,工具集,执行挂钩,和围绕模型的上下文管理支架)是代理的关键决定因素...
Agent harnesses (the system prompt, tool set, execution hooks, and context-management scaffolding around a model) are a critical determinant of agenti...
A Data-Driven Framework for Identifying and Prioritizing RPA Opportunities in Healthcare Processes
机器人流程自动化 (RPA) 被广泛用于减轻美国医院的行政负担,，但估计有 30-50% 的 RPA 计划...
Robotic Process Automation (RPA) is widely used to reduce administrative burden in United States hospitals, yet an estimated 30-50% of RPA initiatives...
Procedural Graphs: Self-Evolving Execution Structures for LLM Agents
大型语言模型越来越多地被部署为能够进行长期规划并通过外部工具执行操作的代理。大多数代理选择行动通过...
Large language models are increasingly deployed as agents that plan over long horizons and act through external tools. Most agents select actions thro...
Don't Drop Dropout: Optimizing Layer Sparsity for Efficient LLM Training and Inference
Layer dropout (a.k.a.随机深度) 已被证明可以实现更快的训练, 更高的准确性, 以及对零样本层剪枝的鲁棒性...
Layer dropout (a.k.a. stochastic depth) has been shown to enable faster training, higher accuracy, and robustness to zero-shot layer pruning in both l...
Testing Interchangeability in LLM Agent Teams
Production multi-agent systems replace agents constantly, on the assumption that an agent filling a role is interchangeable with any other agent that ...
Production multi-agent systems replace agents constantly, on the assumption that an agent filling a role is interchangeable with any other agent that ...
GUT: Quantifying and Optimizing the Reasoning Uncertainty of LLMs via Graph Complexity
近年来，大型语言模型(LLMs) 的推理能力取得了巨大进步。然而, LLM的推理过程通常...
Recent years have witnessed great advances in the reasoning ability of Large Language Models (LLMs). However, the reasoning processes of LLMs often ex...
Beyond Aggregate Scores: Behavioral Correctness Assumptions for Assessing Reference-Based Automatic Evaluation Methods
基于参考的自动评估方法在评估自然语言生成系统中发挥着至关重要的作用。现有的元评估主要...
Automated reference-based evaluation methods play a critical role in assessing natural language generation systems. Existing meta-evaluation primarily...
RISE: Recursive Improvement via Self-Extrapolating Policy Distillation
在策略蒸馏(OPD) 为语言模型训练后, 提供密集的, 每个标记监督，但其有效性受到教师的瓶颈......
On-policy distillation (OPD) provides dense, per-token supervision for language model post-training, but its effectiveness is bottlenecked by teacher ...
Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness
楼宇自动化系统生成丰富的传感器数据，但仍然缺乏洞察力，因为异构点命名, 缺少元数据, 和碎片化文档...
Building automation systems generate rich sensor data yet remain insight-poor because heterogeneous point naming, missing metadata, and fragmented doc...