AINeutralarXiv – CS AI · 6h ago6/10
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AGENTCL: Toward Rigorous Evaluation of Continual Learning in Language Agents
Researchers introduce AgentCL, an evaluation framework for assessing continual learning in language agents, along with MemProbe, a memory design method that helps agents accumulate and reuse knowledge across tasks while avoiding interference. The framework uses controlled task streams to rigorously measure how well agents learn and transfer knowledge over time, revealing that current memory designs struggle to balance learning plasticity with stable knowledge reuse.