500 million tokens were burned just to translate the abstracts of 6,000 papers from the top AI conference NeurIPS 2025 and develop two visualization charts.
Let's see how accurate GPT-5.2, the pinnacle of AI technology, is in translating these cutting-edge AI papers.
These tokens, if converted to on-demand API pricing, would be at least $200.
I know this sounds like a bad deal. After all, there are many affordable translation tools available now, and most people who frequently read academic papers simply read the raw text.
But I'm curious, if we use AI to tackle something seemingly absurd, can we achieve a miracle?
I specifically chose the cutting-edge GPT-5.2, hoping it could translate technical terms more accurately (though don't expect 100% perfection).
Besides, as a ChatGPT Pro user, since I have more than enough Coding Agent credit, I might as well use it to run an extreme test.
The final result is that I successfully translated the abstracts of all 6,000+ papers selected for NeurIPS 2025 into Chinese.
To make it easier for everyone to access the information, I also manually created a front-end page and added two visualization charts to assist in filtering:
1. Keyword Association Graph: Clicking on hot keywords such as "reasoning" or "vision-language models" will directly locate related papers, revealing potential research trends and connections.
2. Cross-border Collaboration Network: For example, clicking on the line connecting "Singapore" and "China" will filter out papers co-authored by those two countries. Of course, you'll find that the line connecting China and the US is the thickest, given the sheer number of papers from these two countries.
Since I've already spent $200 on computing power, consider this my treat—I invite you to experience this result firsthand.
This also allows you to test the true performance of GPT-5.2 in translating cutting-edge professional literature under the stress test of 6,000 papers.
Link: randomarea.com/neurips-2025
