45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026U SalernoU TurinUniversità degli Studi di SalernHypergraphsHypergraph Generation with Latent DiffusionValerio Di Pasquale, Alessia Antelmi, Mirko Polato, Carmine SpagnuoloSydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 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
91%Must read?Must readVote to see the scoreNeurIPS 2026SamsungU TurinU WarsawAI oversight & deceptionReading the Finetuning Prior: Verbatim Content Recovery via Contrastive Decoding DiffingContrastive Decoding Diffing recovers verbatim implanted facts and pipeline artifacts via output-level logit differences without weight access, outperforming white-box methods 170x faster.Michał Brzozowski, Zuzanna Dubanowska, Enrico Cassano, Neo Christopher ChungSydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet18/20 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: 18 of 20 reviewers recommend itlenient 5/5medium 9/10strict 4/5
91%Must read?Must readVote to see the scoreNeurIPS 2026SpotlightU NeuchatelU NeuchâtelDelft University of TechnologyIBM ResearchU TurinAI oversight & deceptionSafety Reconstructed: Generative Modeling via Masked Diffusion Builds Strong Safety GuardrailsLLaDA-Guard uses masked diffusion to score responses under each safety label and classify by difference, improving calibration, reducing over-defense, and enabling token-level risk localization with 60.7% prompt rewriting success.Gert Lek, Abele Mălan, Chaoyi Zhu, Pin-Yu Chen and 2 moreSydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet17/20 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: 17 of 20 reviewers recommend itlenient 5/5medium 10/10strict 2/5