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cs.LG2025
Learning by Analogy: A Causal Framework for Composition Generalization
Lingjing Kong, Shaoan Xie, Yang Jiao +6
Compositional generalization -- the ability to understand and generate novel combinations of learned concepts -- enables models to extend their capabilities beyond limited experien…
cs.LG2025
Enabling Pareto-Stationarity Exploration in Multi-Objective Reinforcement Learning: A Multi-Objective Weighted-Chebyshev Actor-Critic Approach
Fnu Hairi, Jiao Yang, Tianchen Zhou +6
In many multi-objective reinforcement learning (MORL) applications, being able to systematically explore the Pareto-stationary solutions under multiple non-convex reward objectives…
cs.IR2025
Multi-modal Relational Item Representation Learning for Inferring Substitutable and Complementary Items
Junting Wang, Chenghuan Guo, Jiao Yang +3
We study the problem of inferring substitutable and complementary items, which underpins applications such as alternative and follow-up purchase suggestions. Existing approaches ty…