The field of large language models (LLMs) is rapidly evolving, with a growing focus on specialized applications such as conversational search engines, medical research, and legal analysis. Recent studies have demonstrated the potential of LLMs to improve search engine optimization, predict early-onset colorectal cancer, and identify hallmarks of immunotherapy in breast cancer abstracts. Additionally, benchmarks such as C-SEO Bench and DeepResearch Bench have been developed to evaluate the capabilities of LLM-based agents in various domains. Noteworthy papers in this area include C-SEO Bench, which highlights the limitations of current C-SEO methods and the effectiveness of traditional SEO strategies, and ImmunoFOMO, which shows that pre-trained language models can outperform large language models in identifying specific concepts. Furthermore, DeepResearch Bench provides a comprehensive benchmark for evaluating the capabilities of deep research agents, and Ace-CEFR introduces a dataset for automated evaluation of linguistic difficulty in conversational texts. Overall, these studies demonstrate the significant potential of LLMs to advance various fields and improve decision-making processes.