45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026JinanRepresentation & contrastive learningLearning Event-to-Field Operators Without Interpolationxingyu shaSydney 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
57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026GuangzhouJinanAdversarial robustnessAdversarial Attack and Defense for Machine Learning in Statistical PhysicsZhao-Rong Lai, Qiantong Liang, Jian WengSydney 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
57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026JinanDalian University of TechnologyRepresentation & contrastive learningpyCD: A Unified Benchmark for Reliable Evaluation of Cognitive Diagnosis ModelsYouheng Bai, Xueyi Li, Tengteng Cheng, Mingliang Hou and 3 moreSydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 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 0/5medium 0/10strict 1/5
45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026JinanDalian University of TechnologyDatasets & benchmarksMathCD: A Benchmark Dataset for Cognitive Diagnosis with Semantic InformationXueyi Li, Youheng Bai, Tengteng Cheng, Mingliang Hou and 4 moreSydney 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
57%Worth a look?Worth a lookVote to see the scoreNeurIPS 2026JinanJilinDalian University of TechnologyAI in educationAn Information-Theoretic Evaluation Framework for Benchmark and Model Diagnosis in Knowledge TracingHouru Jiang, Zixi Wang, Tengteng Cheng, Xueyi Li and 5 moreParis 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 2026PekingJinanDomain adaptationCross-Domain Knowledge Separation and Positive Transmission for Noisy Domain Incremental LearningKunlun Xu, Zhengyuan Cai, Jiahuan ZhouSydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 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
83%Must read?Must readVote to see the scoreNeurIPS 2026JilinAdelaideRMITJinanRoyal Melbourne Institute of TecDynamic graphsUFO: A Unified Flow-Oriented Framework for Robust Continual Graph LearningUFO proposes a flow-oriented continual graph learning framework that combats catastrophic forgetting and noisy-label-induced catastrophic remembering via generative replay and instance reliability scoring, outperforming baselines across benchmarks.Danhui Zhang, Zhe Wang, Qing Qing, Jiarui Liu and 5 moreSydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet13/20 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: 13 of 20 reviewers recommend itlenient 5/5medium 8/10strict 0/5