Multilingual Clinical Dialogue Summarization and Information Extraction with Qwen-1.5B LoRA

AbstractThis paper describes our submission to theNLP-AI4Health 2025 Shared Task on multi-lingual clinical dialogue summarization andstructured information extraction. Our systemis based on Qwen-1.5B Instruct fine-tuned withLoRA adapters for parameter-efficient adapta-tion. The pipeline produces (i) concise Englishsummaries, (ii) schema-aligned JSON outputs,and (iii) multilingual Q&A responses. TheQwen-based approach substantially improvessummary fluency, factual completeness, andJSON field coverage while maintaining effi-ciency within constrained GPU resources.