Announcing an update to Pangram Text, state-of-the-art AI text detection. Pangram Text now officially supports the top 20 languages on the internet, and performs well on many other languages outside of that! See the thread for technical detail on how we did it! 1/5
📢 WHE is proud to announce our new partnership with Pangram Labs! @pangramlabs In 2025, we updated our Editorial Policy to address the use of AI: “In accordance with our AI Policy, all article submissions must be written by humans; we do not accept AI-generated or AI-assisted…
Our merch came in! Is now a good time to announce that I’m joining @pangramlabs as their Founding Research Scientist after graduation?
Pangram 2.0 is out! @pangramlabs now exhibits significantly stronger performance on heterogeneous mixed text with an an algorithm that performs a more precise search to find the boundary between AI and human text. Also, we got a big UI refresh!
We can now quantify the magnitude of AI edits in a text! Coming soon to Pangram.
As a case study, we built a dataset by applying 9 different Grammarly edits to the same text. According to EditLens, “Fix any mistakes” is the most mild change, while “Make it more detailed” and “Summarize it” are the most invasive. 7/
Presented at PRC10: Using @pangramlabs' #AI detection tool, @AACR detected 36% of abstracts contained at least some #LLM text though authors disclosed use for only 9% of the papers studied. Learn more: science.org/content/articl… @devanko @royperlis @NewsfromScience @ScienceMagazine
AI-generated text is everywhere: hard for orgs to assess human performance. Can we detect it while min false accusations? Yes! With @alexolegimas we audit detectors, show incredible accuracy ~0 (!!) false pos & neg; and we offer a policy framework for evaluating trade-offs. 🧵
Can you believe it’s already time for our summer Media Mixer? On August 21st, we’re partnering with @pangramlabs, the AI detection tool created by researchers at Stanford, Tesla, and Google, to bring you a Media Mixer for the books.
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