Full papers
Submissions are accepted via OpenReview for presentation at the workshop, with no further description provided, but the context implies standard academic paper formats suitable for interdisciplinary exchange.
Machine Learning/CORE Unranked
RCMLR 2026
Responsible Communication of Machine Learning Research in Biomedicine
The RCMLR 2026 workshop, part of NeurIPS 2026, addresses the critical gap between machine learning research in biomedicine and its communication to clinicians, policymakers, and other non-ML stakeholders. It fosters interdisciplinary dialogue to improve the responsible translation of ML findings, countering hype and misinterpretation through evidence-based communication approaches grounded in real-world case studies.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Research areas in scope
01
Responsible Communication in Biomedical ML
Miscommunication of ML capabilities in biomedical contextsHype and overstatement in ML claimsClinical deployment and limitations of decision-support toolsLLMs and medical benchmark performance vs. real-world impactInterdisciplinary translation challenges between ML researchers and domain expertsReporting standards (e.g., TRIPOD+AI, TRIPOD-LLM) and low adherenceCommon language and vocabulary gaps across ML, clinical, and policy communitiesScience communication and journalism in biomedical ML
Policies worth checking twice
- Submissions are handled via OpenReview
- Review process is blind (implied by standard OpenReview practice and workshop context)
- Submission deadline is 29 August 2026 (AOE)
- Author notifications are scheduled for 29 September 2026 (AOE)
- Workshop is part of NeurIPS 2026, implying adherence to NeurIPS policies on dual submission and authorship
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026