datumo/CAC-CoT

CAC-CoT（连接感知紧凑链式思维）数据集是基于论文连接感知紧凑链式思维用于双系统认知任务的有效推理数据综合创建的。该数据集用于训练和评估模型在强调紧凑性和连接意识的链式思维轨迹的推理任务上的表现。数据集支持学习推理轨迹，提高效率（更短的轨迹）同时保持性能，特别是在需要直觉（快速）和分析（慢速）推理的任务上。

The CAC-CoT (Connector-Aware Compact Chain-of-Thought) Dataset is created based on the paper Connector-Aware Compact Chain-of-Thought for Efficient Reasoning Data Synthesis Across Dual-System Cognitive Tasks. This dataset is for training and evaluating models on reasoning tasks with chain-of-thought traces that emphasize compactness and connector awareness. It supports learning reasoning trajectories, improving efficiency (shorter traces) while maintaining performance, especially on tasks that require both intuitive (fast) and analytical (slow) reasoning.