Systematic Literature Reviews (SLRs) and Mapping Studies (MSs) are an established feature of academic Software Engineering literature. But for new, exciting advances in the area there is a tension between supporting fellow academics with reviews that provide a roadmap of the area/timely synthesis of the available evidence, and the maturity of the literature relied on for those reviews. The increasingly prevalent use of preprint databases such as arXiv in Computer Science, for the immediate publication of results, suggests that this tension deserves evaluation and this paper does so through the lens of LLMs4SE: Large Language Models for Software Engineering. Specifically, this paper reports on the initial wave of SLRs and MSs covering LLMs4SE. It directs its analysis at identifying the proportion of arXiv preprints the existing surveys employ, identifying any additional quality assurance measures applied to those preprints, and tracing any subsequent peer-reviewed publications of those preprints. Our initial review found a small number of surveys in the area, congruent with LLMs recent growth as a significant tool in software engineering. The reviews that do exist rely on a significant proportion of pre-prints, and meaningful quality criteria are rarely applied to mitigate against this reliance. We note that although a significant proportion of the preprints are subsequently published in peer-reviewed fora, a significant number are not. In cases where the preprints have been subsequently published in peer-reviewed fora, consistency between the assertions made in the review and the peer-reviewed article was high.