Rohan Paul (@rohanpaul_ai) · 10/10/2026, 13:45:58
Tokyo Metropolitan University Study: Pangram Misses 79.8% of Meta Muse-Glimmer Rewritten Abstracts
A new study from Tokyo Metropolitan University reveals that the AI-text detector Pangram missed 79.8% of scientific abstracts rewritten by Meta's Muse-Glimmer model, while maintaining a near-zero false positive rate on human-written texts. The findings demonstrate that detection efficacy is heavily dependent on the specific LLM used for rewriting, with Pangram catching 93.5% of GPT-5 rewrites but failing significantly against newer models, highlighting critical generalization gaps in current AI detection tools.
SOURCE COVERAGEFull Original Report
Rohan Paul (@rohanpaul_ai) · 2026-10-10 05
Pangram, the AI-text detector, missed 79.8% of scientific abstracts rewritten by Meta's Muse-Glimmer, while flagging just 1 of 5,000 human abstracts.
In a new paper from Tokyo Metropolitan University, reseaerchers find the share of AI-rewritten abstracts that Pangram misses depends strongly on the LLM version
Shows that it caught 93.5% of GPT-5 rewrites but missed 79.8% from another new model. Its miss rate depended mostly on which model did the rewriting.
