Abstract: We analyze the stability of the logit evolutionary dynamics in population games, possibly with multiple heterogeneous populations. For general population games, we prove that, on the one ...

Abstract: Logit adjustment is an effective long-tailed visual recognition strategy to encourage a significant margin between rare and dominant labels. Existing methods typically employ the globally ...

Execute the following commands in the terminal: Enter the unitree_sdk2_python directory, set CYCLONEDDS_HOME to the path of the cyclonedds you just compiled, and then install unitree_sdk2_python. The ...

在当今人工智能迅速发展的时代，单一的大语言模型（LLM）已经无法满足多样化的需求。为了应对这一挑战，华盛顿大学的冯尚彬教授团队联合斯坦福大学、哈佛大学等顶尖研究机构，推出了一个开创性的多模型协同框架——MoCo（Model Collaboration）。这一框架的目标是通过不同的模型协同工作，创造出更为强大的组合式人工智能系统。

在训练与开发单个通用大语言模型 (LLM) 之外，越来越多的研究开始关注多模型协同(model collaboration)：由不同群体、基于不同数据、以不同目的训练的多个大语言模型，通过多样化的协同算法与系统架构，形成组合式人工智能系统。

The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...