ChatGPT correctly identified missing sentences in a partially censored translation and correctly judged a complete translation as complete in a control condition, demonstrating that LLMs are a viable complementary detection method. The paper notes that having multiple independent detection approaches (NLP alignment, bitext mining, LLM-based reasoning) improves overall robustness by enabling cross-validation.
From 2023-streisand-where — Where Have All the Paragraphs Gone? Detecting and Exposing Censorship in Chinese Translation
· §4 Discussion / Appendix C
· 2023
· Free and Open Communications on the Internet
Implications
LLM-based censorship detection can be integrated into automated audit pipelines as a high-recall second-pass over candidates flagged by embedding-based alignment, reducing false negatives without requiring human review for every document.
Ensemble detection (combining NLP alignment with LLM reasoning) is more robust than any single method and should be the architecture target for production translation-censorship monitoring tools.