TuringBench is a benchmark environment that contains :

• Benchmark tasks- Turing Test (i.e., human vs. machine) and Authorship Attribution: (i.e., who is the author of this texts?)
• Datasets (Binary and Multi-class settings)
• Website with leaderboard

The dataset has 20 labels (19 AI text-generators and human). We built this dataset by collecting 10K news articles (mostly Politics) from sources like CNN and only keeping articles with 200-400 words. Next, we used the Titles of these human-written articles to prompt the AI text-generators (ex: GPT-2, GROVER, etc.) to generate 10K articles each. This gives us a sum total of 200K articles and 20 labels. However, since there are two benchmark tasks - Turing Test and Authorship Attribution settings, we have all 20 labels in one dataset for the multi-class setting and only human vs. one AI text-generator, making 19 binary-class datasets.