Exploring the System 1 Thinking Capability of Large Reasoning Models

Understand

This paper explores the system 1 thinking capability of Large Reasoning Models (LRMs), the intuitive ability to respond efficiently with minimal token usage.

• While existing LRMs rely on long-chain reasoning and excel at complex tasks, their system 1 thinking ability remains largely underexplored.
• This capability is essential as it reflects models' difficulty awareness and reasoning efficiency, both critical for real-world applications.
• We propose S1-Bench, a multi-domain, multilingual benchmark comprising model-simple system 1 questions.