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cs.LG2026
Task-Differentiated Atomic Skill Expansion and Routing for Continual Learning Across Highly Heterogeneous Tasks
Jiacheng Wang, Xinjia He, Qi Ding +5
Continual learning (CL) is commonly studied under the assumption that sequential tasks are semantically related or structurally similar. However, in highly heterogeneous settings,…
cs.LG2026
Diversity-Driven Offline Multi-Objective Optimization via Nested Pareto Set Learning
Yiyi Zhu, Yaolin Wen, Xiang Xia +6
Multi-objective optimization (MOO) has emerged as a powerful approach to solving complex optimization problems involving multiple objectives. In many practical scenarios, function…