Introduction to the Workshop

The rapid evolution of Large Foundation Models (LFMs) has transformed the landscape of biomedical research, clinical decision-making, and healthcare innovation. From decoding complex biological interactions to assisting in diagnosis and drug discovery, LFMs have demonstrated remarkable potential across a broad spectrum of biomedical applications. However, their adaptation to this highly specialized and sensitive domain presents unique challenges ranging from data scarcity and heterogeneity to issues of interpretability, fairness, and reproducibility. The Workshop on Large Foundation Models for Biology and Biomedicine (LFMBio 2026) aims to bring together researchers, practitioners, and industry experts to advance the science and practice of applying LFMs to biomedical problems. The workshop will serve as a forum for presenting original research, fostering interdisciplinary dialogue, and exploring cutting-edge innovations in model design, multimodal integration, trustworthiness, and ethical deployment. We invite contributions that span foundational model development, performance optimization, knowledge representation, real-world clinical applications, and the societal impact of these powerful technologies.

 WORKSHOP CHAIRS

Call for Papers

We invite original research contributions related to Large Foundation Models (LFMs) for biology and biomedicine in (but not limited to) the following areas:

• Model Development and Adaptation

  • Pre-training and fine-tuning LFMs for biomedical and clinical domains

  • Multimodal data acquisition, curation, and annotation

  • Development, scalability, and optimization of architectures for biomedical data analysis
    
    

• Performance Enhancement Techniques

  • Prompt engineering, chain-of-thought (CoT) reasoning, and retrieval-augmented generation (RAG)

  • Reinforcement learning with human feedback (RLHF)

  • Data resampling for class balancing and integration of auxiliary weak learner models
    
    

• Knowledge Engineering and Representation

  • Generating knowledge graphs, biological networks, ontologies, and taxonomies

  • Multimodal alignment for biomedical question answering and decision support
    
    

• Applications in Biomedicine and Healthcare

  • Clinical risk prediction, disease diagnosis and prognosis, surgical planning, and personalized treatment

  • Drug discovery, pharmacogenomics, and personalized medicine

  • Biomedical imaging applications (radiology, pathology, histology, cells, transcriptomics, etc.)

  • Visual reasoning and question answering in clinical and biological domains

  • Nutrition-focused applications (dietary assessment, calorie estimation, meal analysis)

  • Case studies and real-world deployment in healthcare
    
    

• Evaluation, Benchmarking, and Reproducibility

  • Creation of benchmark datasets and evaluation metrics

  • Reproducibility challenges in biomedical LFM research
    
    

• Trustworthiness, Ethics, and Societal Impact

  • Trustworthiness, explainability, hallucination, and validation of results

  • Equity, fairness, bias, safety, and reliability in biomedical applications

  • Ethical considerations and interpretability of LFMs

Submission Guidelines

Please check: Call for Papers

All accepted papers will be published in the WACV Workshop 2026 proceedings and made publicly available approximately two weeks before the main WACV 2026 conference. 

ACKNOWLEDGEMENT: The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.