The second Workshop on Case-Based Reasoning and Large Language Model Synergies (CBR-LLM) continues to explore the dynamic intersection between Case-Based Reasoning (CBR) and Large Language Models (LLMs), building upon the foundational discussions initiated in our first workshop at ICCBR 2024. As the collaboration between these two areas matures, particularly given the rapid growth of LLM research, researchers and practitioners gather again to share new findings, challenges, and emerging insights into their combined potential. A community of CBR-LLM researchers has been working on a joint paper titled “Case-Based Reasoning Meets Large Language Models: A Research Manifesto For Open Challenges and Research Directions” since the last workshop, which is available as a preprint at HAL (https://hal.science/hal-05006761v1). This collaborative efort captures current progress, open challenges, and future research directions at the intersection of CBR and LLMs. At this year's CBR-LLM workshop, we expect to further discuss potential research opportunities for integrating CBR and LLMs. We believe that CBR methods can play an essential role in enhancing LLM performance, particularly by refining prompt engineering, reducing hallucinations, and enabling persistent memory of conversational interactions. This mutual enhancement underscores the significant promise of continued collaboration and research at the intersection of CBR and LLMs.