Meta’s TextSeal2 improves detection of AI-generated text with new watermarking technique

Copula mixing pushes detection rates past 89% while adding zero latency to AI inference pipelines On October 29, 2026, researchers at Meta’s FAIR lab and the Meta Superintelligence Labs published a paper on arXiv introducing TextSeal2, a next-generation watermarking technique for large language models. The system detected 89% of 200-token AI-generated outputs at a false-positive rate of just 0.1%, a result that meaningfully clears the bar set by its predecessors. What TextSeal2 actually does differently The original TextSeal, released in August 2026, embedded detectable signals into AI text by manipulating how models select words during generation. TextSeal2 sidesteps that trade-off using a technique called copula mixing. Rather than maintaining multiple separate secret keys, the system consolidates them into a single virtual key while simultaneously injecting fresh noise into the process. The practical result is a stronger, more consistent signal baked into the text, without forcing the model to slow down or produce blander outputs. Crucially, TextSeal2 adds no measurable inference latency and preserves speculative decoding acceptance rates. Speculative decoding is a speed optimiz...