AI Scientist-v2 Achieves Peer-Reviewed Publication without Human Intervention

The Future of The AI Scientist 

We believe the next generations of The AI Scientist will usher in a new era in science. That AI can generate an entire scientific paper that passes peer-review at a top-tier ML workshop conveys very promising early signs of progress. But this is just the beginning. We expect AI to continue to improve, potentially exponentially. At some point in the future, AI will probably be able to generate papers at and beyond human levels, including at the highest level of scientific publishing. We predict The AI Scientist and systems like it will create papers worthy of acceptance not only at top ML conferences, but also in the top journals in science. 

Ultimately, we believe what matters most is not how AI science is judged vs. human science, but whether its discoveries aid in human flourishing, such as curing diseases or expanding our knowledge of the laws that govern our universe. We look forward to helping usher in this era of AI science contributing to the betterment of humanity. 

Sakana AI’s AI Scientist-v2 has made history by becoming the first AI system to autonomously generate a scientific paper that passed peer review at the ICLR 2025 workshop titled “I Can’t Believe It’s Not Better: Challenges in Applied Deep Learning.” This milestone underscores the potential of AI in automating complex research processes. 

Technical Highlights:

  • Agentic Tree Search: Utilizes a progressive agentic tree-search methodology to explore research pathways. 
  • Vision-Language Model Feedback: Incorporates VLM feedback loops for refining content and visuals. 
  • Open-Source: The codebase is available for public use and further development. 

Key Contributors:

Yutaro Yamada, Robert Tjarko Lange, Cong Lu, Shengran Hu, Chris Lu, Jakob Foerster, Jeff Clune, and David Ha. 

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