KDD 2026 - Semi-Supervised Text-Attributed Graph Distillation @TheOfficialACM
KDD 2026 - Semi-Supervised Text-Attributed Graph Distillation @TheOfficialACM
Uploaded July 2026 | Updated September 2026, 2 weeks ago
Yurui Lai, Samir Moustafa, Renchi Yang, Tsz Nam Chan
KDD 2026 - Semi-Supervised Text-Attributed Graph DistillationVinicius Pereira on The Need For Linguistic DiversityKDD 2026-DIREC: Diffusion-Based Review-Embedding Generation for Accurate Cross-Domain RecommendationKDD 2026 - Benchmarking Table Extraction from Heterogeneous Scientific PDF DocumentsKDD2026-LATTE:Learning AdaptiveSegmentation for Efficient and EffectiveTrajectory SimilarityLearningKDD 2026 - Out-of-Distribution Robust Explainer for Graph Neural NetworksKDD 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-AGI
Association for Computing Machinery (ACM) |

KDD 2026 - Semi-Supervised Text-Attributed Graph Distillation

SHARE TO X SHARE TO REDDIT SHARE TO FACEBOOK WALLPAPER