KDD 2026 - Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification? @TheOfficialACM
KDD 2026 - Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification? @TheOfficialACM
Uploaded July 2026 | Updated September 2026, 2 weeks ago
Fei Lin, Ziyang Gong, Cong Wang, Tengchao Zhang, Yonglin Tian, Yining Jiang, Ji Dai, Chao Guo, Xiaotong Yu, Xue Yang, Gen Luo, Fei-Yue Wang
KDD 2026 - Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?KDD2026-SciHorizon-DataEVA:AnAgenticSys. to ScalableAI-Readiness Eval. of Heterogeneous Scient. DataPeople of ACM: Russ Cox (8/11/2026)KDD 2026-CORF-Net: Cross-Order Representation Fusion Network for Denoised Survey Response ModelingKDD2026-Deformation Local. TheoryGuided TransferLearning for Mining-inducedSeism.Risk ZonePredictionKDD 2026 - ARC-TGI: Human-Validated Task Generators with Reasoning Chain Templates for ARC-AGIKDD2026-DeepTaxon:AnInterpretableRetrieval-AugmentedMultimodal Framework forUni.SpeciesIdent.andDis.KDD 2026-HDMoE:A HierarcalDecoupling-FusionMixture-of-Experts FrameworkforMultim.CancerSurvivalPred.KDD 2026 - MFC: Mixed Federated Clustering based on Cross-modal Feature DecouplingKDD 2026 - KLAN: Kuaishou Landing-page Adaptive Navigator
Association for Computing Machinery (ACM) |

KDD 2026 - Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?

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