6 papers
STAIL: Semantic Text-Anchored Incremental Learning for Medical Imaging via Large Language Models
Songpan Gao, Yajie Zhang, Guanxing Chen +9
Deep learning models applied to medical image analysis suffer from severe catastrophic forgetting when continually adapting to new clinical tasks in dynamic environments. Mainstrea…
PathMem: Toward Cognition-Aligned Memory Transformation for Pathology MLLMs
Jinyue Li, Yuci Liang, Qiankun Li +7
Computational pathology demands both visual pattern recognition and dynamic integration of structured domain knowledge, including taxonomy, grading criteria, and clinical evidence.…
QM-ToT: A Medical Tree of Thoughts Reasoning Framework for Quantized Model
Zongxian Yang, Jiayu Qian, Kay Chen Tan +4
Large language models (LLMs) face significant challenges in specialized biomedical tasks due to the inherent complexity of medical reasoning and the sensitive nature of clinical da…
Better Eyes, Better Thoughts: Why Vision Chain-of-Thought Fails in Medicine
Yuan Wu, Zongxian Yang, Jiayu Qian +5
Large vision-language models (VLMs) often benefit from chain-of-thought (CoT) prompting in general domains, yet its efficacy in medical vision-language tasks remains underexplored.…
CoT2-Meta: Budgeted Metacognitive Control for Test-Time Reasoning
Siyuan Ma, Bo Gao, Zikai Xiao +6
Recent test-time reasoning methods improve performance by generating more candidate chains or searching over larger reasoning trees, but they typically lack explicit control over w…
Med-REFL: Medical Reasoning Enhancement via Self-Corrected Fine-grained Reflection
Zongxian Yang, Jiayu Qian, Zegao Peng +4
Large reasoning models excel in domains like mathematics where intermediate reasoning is straightforward to verify, but struggle to self-correct in medicine fields where evaluating…