Truth and Regret: Large Language Models, the Quran, and Misinformation

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Notes

1 On Inimitability see Richard C. Martin, “Inimitability,” in Encyclopaedia of the Qurʾān, ed. Johanna Pink (Leiden: Brill). Consulted online on 22 August 2023, http://dx.doi.org.bham-ezproxy.idm.oclc.org/10.1163/1875-3922_q3_EQCOM_00093. 

2 On tahrif see Shari Lowin, “Revision and Alteration,” in Encyclopaedia of the Qurʾān, ed. Johanna Pink, (Leiden: Brill). Consulted online on 22 August 2023, http://dx.doi.org.bham-ezproxy.idm.oclc.org/10.1163/1875-3922_q3_EQSIM_00358.

3 When asking the standard English version of ChatGPT-3.5 to cite verses in Arabic we apparently hit a guardrail. “I apologize for any confusion caused. However, as an AI language model, I do not have direct access to the Quran in Arabic or the ability to cite specific verses. I can provide general information and interpretations based on my training, but for precise citations and detailed analysis of specific verses, I recommend consulting a qualified Islamic scholar or referring to trusted translations and commentaries of the Quran.”

4 It is worth noting that the misquotations arising from Bard are especially concerning, as Bard is given access to the Google API when composing responses and can cite its answers with specific website links. Instead of linking to reputable sources for Quranic translations or source text, the links provided by Bard were often broken or led to social media posts on Facebook or other platforms.

5 On STS models see Nils Reimers and Iryna Gurevych, “Sentence-BERT: Sentence embeddings using siamese BERT-networks.” arXiv 1908.10084 (2019). The pre-trained STS model is available for download on HuggingFace at the following URL: https://huggingface.co/sentence-transformers/stsb-xlm-r-multilingual

6 Cosine distance is a common method for comparing two vectors u and v in a variety of contexts. Vectors can be thought of as a directed line segment that possesses both magnitude and direction. A cosine distance metric seeks to compare the difference in direction between a set of vectors, which can be written as the cosine of the angle required to change the direction of one vector into the direction of the other. For a variety of NLP models that rely on embeddings of words, passages, or entire documents, the cosine distance metric serves as a proxy for measuring the overall semantic similarity of these entities.

7 A BiLingual Evaluation Understudy (BLEU) score is calculated by combining a series of precision scores with a brevity score. Precision can be calculated at the single word (1-gram) level by taking the ratio of correctly matching words in the prediction to the total number of words in the source. A brevity score penalizes predictions which exceed the word length of the source. For further detail on BLEU see Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu, “Bleu: a Method for Automatic Evaluation of Machine Translation,” in Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, ed. Pierre Isabelle, Eugene Charniak and Dekang Lin (Philadelphia: Association for Computational Linguistics, 2002), 311–18.

8 Assessing LLM performance across languages is commonly done using the “Measuring Massive Multitask Language Understanding” (MMLU) benchmark. See See Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt, “Measuring Massive Multitask Language Understanding.” arXiv 2009.03300v3 (2021). 

9 For more information on the problem of model collapse, see Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, Ross Anderson, “Model Dementia: Generated Data Makes Models Forget” arXiv preprint arXiv:2305.17493 (2023).