57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026U WarsawUniwersytet Warszawski ul. KrakoCMU, Carnegie MellonMerck Healthcare KGaAHelmholtz Munich GmbHGenomics & single-cellImmuVis: Hyperconvolutional Foundation Models for Imaging Mass CytometryDawid Uchal, Marcin Możejko, Krzysztof Gogolewski, Piotr Kupidura and 13 moreSydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet1/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 1 of 20 reviewers recommend itlenient 1/5medium 0/10strict 0/5
67%Highly rated?Highly ratedVote to see the scoreNeurIPS 2026JagiellonianHelmholtz Zentrum München GmbH FJohns Hopkins University, UniBo,Johns HopkinsNational Medical Institute of thVision-language modelsAnatomy-Activated Mixture-of-Experts for 3D Medical Vision-Language Pre-trainingSzymon Płotka, Gizem Mert, Pedro R. A. S. Bassi, Wenxuan Li and 8 moreParis Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026– ReadersNo votes yet2/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 2 of 20 reviewers recommend itlenient 2/5medium 0/10strict 0/5
74%Highly rated?Highly ratedVote to see the scoreNeurIPS 2026Helmholtz MunichTechnische Universität MünchenHelmholtz Zentrum MünchenTechnical University of MunichHelmholtz Munich GmbHMolecules & drug discoverySample Efficient Generative Molecular Optimization with Joint Self-ImprovementJoint Self-Improvement uses a joint generative-predictive model and self-improving sampling to reduce distribution shift and efficiently generate optimized molecules under limited evaluation budgets.Serra Korkmaz, Adam Izdebski, Jonathan Pirnay, Rasmus Møller-Larsen and 5 moreSydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet9/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 9 of 20 reviewers recommend itlenient 5/5medium 4/10strict 0/5