Infoxmed2.0-27B: Instruction Tuning, Preference Alignment, and GRPO-Based Reward Model Training for Medical LLMs
The paper introduces Infoxmed2.0-27B, a medical foundation model derived from Qwen3.5-27B that achieves superior performance on medical benchmarks through a rigorous multi-stage post-training pipeline involving proprietary data synthesis, LoRA-based instruction tuning, DPO preference alignment, and GRPO-based reward model training.