AINeutralarXiv – CS AI · 10h ago6/10
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Task-Differentiated Atomic Skill Expansion and Routing for Continual Learning Across Highly Heterogeneous Tasks
Researchers introduce TASER, a continual learning framework designed to handle highly heterogeneous tasks by dynamically expanding atomic skills and routing them based on task requirements. The work addresses catastrophic forgetting in AI systems learning sequential tasks with diverse reasoning patterns, validated on a new benchmark called HeteroCLBench comprising 19 tasks across 9 cognitive dimensions.