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• The approach requires more extensive real-world testing to handle practical variations and edge cases.limitation 85%
• The proposed lifelong imitation learning framework achieves 10-17 point gains in AUC on the LIBERO benchmarks compared to previous leading methods.result 95%
• The framework reduces forgetting by up to 65% compared to previous leading methods.result 95%
• The approach uses multimodal latent replay that stores compact representations of visual, linguistic, and robot's state information instead of raw data.method 90%
• The incremental feature adjustment mechanism uses angular margin constraints to regularize the evolution of task embeddings and preserve inter-task distinctiveness.method 90%
• The method has limitations including potential over-dependence on pre-trained models.limitation 85%
• Ablation studies confirm the effectiveness of each component, showing consistent gains over alternative strategies.result 80%
• The method could replace or enhance existing robotic systems that follow static programming by enabling continuous adaptation without requiring complete retraining.market 75%

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