SIGIR 2024 W1.2 [fp] Large Language Models are Learnable Planners for Long-Term Recommendation @TheOfficialACM
SIGIR 2024 W1.2 [fp] Large Language Models are Learnable Planners for Long-Term Recommendation @TheOfficialACM
Updated September 2026, 6 days ago
SIGIR 2024 W1.2 [fp] Large Language Models are Learnable Planners for Long-Term RecommendationKDD 2026 - Advancing Graph Few-Shot Learning via In-Context LearningKDD 2026 - Invariant-Stratified Propagation for Expressive Graph Neural NetworksThe American Disability Act Signed - July 26, 1990KDD 2026 - A Geometric Information Bottleneck for Activation SteeringPreventing Retry Storms in AI-Assisted MicroservicesKDD 2026 - AlphaSearch: Agentic AI for Price Arbitrage in Energy SystemsKDD 2026-Discrimi. Anchor Learning with DistributionAlignment for Multi-modal RemoteSensingClusterigKDD 2026-IterativeProbab.HoughTransform:RobustDiscovery of FilamentaryStructures inHigh-NoiseRegimesAugust 2026 CACM: Neural Coding as Software Engineering Augmentation, Not AbdicationCAIS 2026 | Welcome and Opening RemarksKDD 2026 - SimuGov: A Simulation Optimization Framework for Generative AI Governance Strategy Design
Association for Computing Machinery (ACM) |

SIGIR 2024 W1.2 [fp] Large Language Models are Learnable Planners for Long-Term Recommendation

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