57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026University Paris SaclayEcole polytechnique, IP ParisTélécom ParisUniversité Paris-SaclayVideo generationAR-Edit: Training-Free Streaming Video Editing without InversionHovhannes Margaryan, Vicky Kalogeiton, Quentin Bammey, Christian SandorParis Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · 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
45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026Université Paris-SaclayUniversité Paris Dauphine - PSLUniversity Paris-SaclayDiffusion modelsEuclidean Score-Based Generative Modeling with Permutation SemanticsGaël Heck, Nassim Bourarach, Sylvie Le Hégarat-Mascle, Nicolas LerméParis Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 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
57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026Université Paris-SaclayENSIIELaboratory of Mathematics and MoENSIIE - CapgeminiBayesian & probabilistic methodsBeyond Imputation: Mask-Adaptive Conformal Prediction via Tree Embeddings on General Missing Data MechanismsJiarong Fan, Juhyun Park, Thi Phuong Thuy Vo, Nicolas BrunelSydney Poster Session 1, Tue, Dec 8, 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
86%Must read?Must readVote to see the scoreNeurIPS 2026Université Paris-SaclayCentraleSupelecLaboratoire de recherche en infoRepresentation & contrastive learningDrive vs. Decay: On the Training Dynamics of Joint-Embedding Predictive ArchitecturesLinearizing JEPA gradient flow reveals competing drive and decay effects that unify collapse-avoidance heuristics and predict a stability phase boundary, leading to ResidualPred, which improves rank and accuracy.José Lucas De Melo Costa, Seong Woo Ahn, Fabrice Popineau, Arpad Rimmel and 1 moreSydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet14/20 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: 14 of 20 reviewers recommend itlenient 2/5medium 10/10strict 2/5