The field of software engineering is witnessing significant developments with the increasing adoption of large language models (LLMs). Recent studies have highlighted the importance of reproducibility in LLM-based research, with a focus on mitigating reproducibility smells and introducing reproducibility maturity models. Additionally, the use of LLMs in software engineering tasks such as vulnerability detection and automated backporting of patches is being explored. However, the reliability and limitations of LLMs in these tasks are still being investigated. Noteworthy papers in this area include the development of ng-reactive-lint, a tool for detecting high-impact anti-patterns in Angular applications, and the introduction of BackportBench, a comprehensive benchmark suite for patch backporting problems. Furthermore, research on the prevalence of LLM-assisted text in scholarly writing and the economies of open intelligence in the model ecosystem is shedding light on the growing impact of LLMs on the research landscape.