KDD 2026 - TAROT: Task-Adaptive Refinement of LLM-prior Graphs for Few-shot Tabular Learning @TheOfficialACM
KDD 2026 - TAROT: Task-Adaptive Refinement of LLM-prior Graphs for Few-shot Tabular Learning @TheOfficialACM
Uploaded July 2026 | Updated September 2026, 2 weeks ago
Ruxue Shi, Yili Wang, Mengnan Du, Hangting Ye, Yi Chang, Xin Wang
KDD 2026 - TAROT: Task-Adaptive Refinement of LLM-prior Graphs for Few-shot Tabular LearningKDD 2026 - UniNote: A Unified Embedding Model for Multimodal Representation and RankingKDD 2025 - MetaEformer: Unveiling and Leveraging Meta-Patterns for Complex and Dynamic SystemsTechnoableism Holds Us All BackKDD 2026 - Aligning Large Language Models with Searcher PreferencesKDD2026-SCALE:Style-CausalDisentang. withAdaptiveLifelongExpert forOnlineLatent-domainAnomalyDetect.KDD 2026 - Structured Inductive Bias for Multi-timescale Knowledge TracingKDD 2026-BiasMap:Lever. Cross-Attentions toDiscoverandMitigateHiddenSocialBiases inText-to-ImageGen.ByteCast Ep80: Andrew Barto & Richard SuttonPeople of ACM: Julia Gersey (12/18/2025)KDD 2026-FLEDA: Forec.-Based Data PartitionPlacement forEfficient Deep Learning Recom.Model TrainingKDD 2026 - HazardFlow: Enhancing Health Status Representations via Score-based Energy Modeling
Association for Computing Machinery (ACM) |

KDD 2026 - TAROT: Task-Adaptive Refinement of LLM-prior Graphs for Few-shot Tabular Learning

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