ARC benchmark (AI2 Reasoning Challenge) Easy (ARC-e) and Challenge (ARC-c): These are two sets of questions from the ARC dataset, designed to evaluate a system’s ability to reason and use knowledge. ARC-e contains easier questions, while ARC-c has more challenging ones, typically requiring more complex reasoning or knowledge.

• AI Education: The ARC benchmark can be used to teach and test the skills of AI students and practitioners. It can help them learn how to design, implement, and evaluate AI systems that can reason and use knowledge to answer questions from various domains.
• AI Evaluation: The ARC benchmark can be used to measure and compare the capabilities of different AI systems, especially large language models (LLMs). It can provide a comprehensive and challenging evaluation of how well these systems can perform on tasks that require reasoning and knowledge.
• AI Innovation: The ARC benchmark can be used to inspire and motivate new research and development in AI. It can provide a platform for exploring new ideas, methods, and applications for AI systems that can reason and use knowledge

• An ARC-e question: What is the name of the process by which plants make sugar from sunlight?
• An ARC-c question: Which of these is a potential application of nanotechnology?
  • A) Creating new types of musical instruments
  • B) Developing treatments for cancer
  • C) Building faster computers
  • D) Improving soil quality for agriculture

• The ARC Benchmark: Evaluating LLMs’ Reasoning Abilities | Deepgram
• Thoughts on the ARC benchmark – Weights & Biases (wandb.ai)