69%Highly rated?Highly ratedVote to see the scoreNeurIPS 2026OxfordWellcome Sanger Institute / UnivSynteny AIU OxfordMolecules & drug discoveryAI for Drug Discovery Models Often Do Not Learn as Expected and How to Diagnose These Failure ModesNikhil Branson, Aaron Wenteler, Guy Durant, Charlotte DeaneSydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet3/20 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: 3 of 20 reviewers recommend itlenient 2/5medium 1/10strict 0/5
45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026EPFL - EPF LausanneOxfordEPFLGraph neural networksHierarchical Graph Representation Learning with Pooling-Induced SubstructuresLuca Sbicego, Xiaowen Dong, Dorina ThanouParis Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026– ReadersNo votes yet0/20 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: 0 of 20 reviewers recommend itlenient 0/5medium 0/10strict 0/5
45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026University College LondonPhysicsXAIDOS Lab, Department of ComputeOxfordInVivoAIGraph neural networksGraph and Simplicial Complex Prediction Gaussian Process via Hodgelet RepresentationsMathieu Alain, So Takao, Bastian Rieck, Xiaowen Dong and 1 moreSydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet0/20 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: 0 of 20 reviewers recommend itlenient 0/5medium 0/10strict 0/5
71%Highly rated?Highly ratedVote to see the scoreNeurIPS 2026U OxfordMax Planck Institute for MultidiInstitue for Advanced Study, PriMax PlancInstitute for MultidiscOxfordGraph generationPermutation-Invariant Spectral Learning via Dyson DiffusionDyson Diffusion Model uses Dyson Brownian motion to shift inductive bias to diffusion dynamics, yielding permutation-invariant spectral learning that improves graph generation.Tassilo Schwarz, Cai Dieball, Constantin Kogler, Renaud Lambiotte and 3 moreSydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet6/20 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: 6 of 20 reviewers recommend itlenient 2/5medium 4/10strict 0/5
71%Highly rated?Highly ratedVote to see the scoreNeurIPS 2026U OxfordMila / Université de MontréalGoogle DeepMind / U. de MontrealMila, U. MontrealUSIMechanistic interpretabilityA Mechanistic Analysis of Looped Reasoning Language ModelsLooped reasoning models converge to cyclic fixed points that stabilize attention and repeat feedforward inference stages iteratively, with recurrence size and normalization affecting stability.Hugh Blayney, Alvaro Arroyo, Johan Obando Ceron, Pablo Samuel Castro and 3 moreSydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face– ReadersNo votes yet6/20 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: 6 of 20 reviewers recommend itlenient 3/5medium 3/10strict 0/5