NLP/CORE Unranked

DAIH 2026

LLM/VLM Deployment Opportunities and Risks in Healthcare

1791518400000San Francisco, CaliforniaOfficial conference site Site reachable

DAIH 2026 is a full-day workshop co-located with COLM 2026 in San Francisco, focused on the responsible deployment of large language and vision-language models in clinical healthcare settings. It brings together researchers, clinicians, and industry professionals to address real-world challenges in safety, equity, operational integration, and post-deployment monitoring of AI systems in medicine.

Official CFP Back to deadlines Verified September 9, 2026

Paper fit

Contribution paths

A strong submission should clearly identify its contribution and evaluate it appropriately.

Research Papers

Up to 8 pages excluding references. Technical work on evaluation, safety, robustness, multimodal modeling, fairness, privacy, governance, monitoring, or workflow integration. Accepted papers will be presented as spotlight talks or posters.

Deployment Case Reports

Up to 4 pages excluding references. Practical accounts from clinical, operational, or industry deployments — including work-in-progress, negative results, and lessons learned. Accepted case reports will be presented as posters.

Research areas in scope

Topics

Real-world deployment and clinical integrationMultimodal clinical reasoning and decision supportHuman–AI collaboration in clinical workflowsOperational integration and workflow designClinical documentation, summarization, and chart reviewPatient-facing communication and health literacyNegative results and failure case analyses from real-world deploymentsLessons learned from industry and health system implementationsSafety and reliabilityClinical evaluation beyond benchmark accuracyHallucination detection, characterization, and mitigation in medical contextsRobustness under temporal, institutional, and demographic distribution shiftFailure-mode characterization and safety monitoringPost-deployment surveillance and error analysisFairness and bias auditing across patient populationsPrivacy-preserving methods for clinical LLM/VLM deploymentRegulatory compliance and emerging governance frameworksAccountability and liability in clinical AI systems

Policies worth checking twice

Submissions must be non-archival.
Papers must use the COLM 2026 LaTeX template.
Review process is double-blind; submissions must be anonymized or will be desk rejected.
Related arXiv papers by the same authors do not break anonymity but must be cited in third person.
Conflicts of interest are managed per COLM policy; conflicted organizers are recused from decisions.
Dual-submission is allowed for ongoing unpublished work or extensions of non-archival presentations, but not for work already published in journals or conference proceedings (including COLM main conference).
Authors must follow COLM 2026 policies on Large Language Model usage.

Official sources

Compiled from the official call for papers. The organizers’ pages remain authoritative.

Official conference site

Last verified September 9, 2026