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The Green List
An interactive explainer app for LLM watermarking
A hands-on, interactive deep dive into LLM text watermarking. Explore the algorithms, generate and detect watermarks, attack them, measure statistical evidence, and test post-hoc watermarking with real models.
AI-generated text is everywhere.
But how can we tell whether a piece of text actually came from an AI model?
And more importantly — **how does watermarking actually work under the hood?**
I built **The Green List** to make that question interactive.
Instead of another blog post with static diagrams, you can actually experiment with LLM watermarking:
🟢 See how a secret key creates a “green list” of tokens
📊 Generate text and inspect z-scores, p-values and per-token evidence
🧪 Test paraphrasing, translation, truncation and adaptive attacks
🧠 Explore entropy, capacity and multi-bit payloads
🎲 Understand Gumbel-max and tournament sampling
🔬 Compare watermarking schemes side-by-side
⚡ Run post-hoc selection watermarking against real models
The interesting part: **the numbers aren't fake.**
The algorithms run directly in the browser, so the charts, statistics, KL divergences, decoded payloads and attack curves are calculated from the actual algorithms rather than pre-rendered illustrations.
I built this because LLM watermarking is going to become increasingly important — but most explanations make the underlying ideas harder to understand than they need to be.
My goal was simple:
**Make the research understandable by letting people play with it.**
🔗 Try it: https://aianytime.github.io/llm-...
💻 Open source: https://github.com/AIAnytime/llm...
Would love to hear from researchers, AI engineers, and educators: **what part of LLM watermarking is hardest to understand?**
About The Green List on Product Hunt
“An interactive explainer app for LLM watermarking”
The Green List was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #149 on the daily leaderboard. A hands-on, interactive deep dive into LLM text watermarking. Explore the algorithms, generate and detect watermarks, attack them, measure statistical evidence, and test post-hoc watermarking with real models.
On the analytics side, The Green List competes within Developer Tools, Artificial Intelligence, GitHub and Tech — topics that collectively have 1.7M followers on Product Hunt. The dashboard above tracks how The Green List performed against the three products that launched closest to it on the same day.
Who hunted The Green List?
The Green List was hunted by AI Anytime. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of The Green List including community comment highlights and product details, visit the product overview.
AI Anytime