1. Research cutting-edge Large Language Model (LLM) technologies, including but not limited to: large language models and their fine-tuning techniques, Retrieval-Augmented Generation (RAG), prompt engineering, and knowledge-based dialogue systems; 2. Improve the overall performance of the foundational models, covering data acquisition, model evaluation, Supervised Fine-Tuning (SFT), reward modeling, and reinforcement learning; 3. Continuously promote the core technological development of large language models, constantly optimizing understanding, reasoning, and generation capabilities; 4. Collaborate with cross-functional teams to integrate and promote advanced LLM solutions.