45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026ETH ZürichKTH Royal Institute of TechnologETH ZurichU CambridgeActive learningForgetting to Improve: Principled Data Removal in Active LearningManuel Wendl, Erik Englesson, Andreas Krause, Carl Henrik EkSydney Poster Session 1, Tue, Dec 8, 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
45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026KTH Royal Institute of TechnologKTH Royal Institute of TechnologFeature attributionExact power indices for plurality-voting ensemblesIlie Sarpe, Theofanis Georgakopoulos, Aristides GionisSydney Poster Session 2, Tue, Dec 8, 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
45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026KTH Royal Institute of TechnologKTH Royal Institute of TechnologBayesian & probabilistic methodsDifferentiable Systematic Resampling for Variational Sequential Monte CarloFredrik Cumlin, Saikat ChatterjeeAtlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · 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 2026KTH Royal Institute of TechnologKTH Royal Institute of TechnologFlow matchingRobust Flow Matching under Target Corruption and Label NoiseMert Can Kurucu, Erik Englesson, Hossein AzizpourParis Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 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
57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026KTH Royal Institute of TechnologAlan Turing InstituteKTH Royal Institute of TechnologAdversarial robustnessThe Adversarial Gait: Detecting Visual Adversarial Attacks against Vision-Language Models via Self-Targeted Gradient CharacterizationMauricio Byrd Victorica, Ezzeldin Shereen, György DánSydney 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
71%Highly rated?Highly ratedVote to see the scoreNeurIPS 2026KTH Royal Institute of TechnologKTH Royal Institute of TechnologGoogle ResearchDomain adaptationDensity-Ratio Losses for Post-Hoc Learning to DeferPost-hoc learning to defer is cast as density-ratio estimation between ideal distributions, yielding adjustable deferral rules that recover Chow's rule and outperform baselines.Alexander Soen, Ragnar Thobaben, Joakim Jaldén, Richard NockSydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 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