Papers with continual learning sub-setups

1 papers
Hierarchical-Task-Aware Multi-modal Mixture of Incremental LoRA Experts for Embodied Continual Learning (2025.acl-long)

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Challenge: Existing continual learning setups for embodied intelligence focus on executing low-level actions, neglecting the ability to learn high-level planning and multi-level knowledge.
Approach: They propose a Hierarchical Embodied Continual Learning Setups (HEC) that divides the agent’s continual learning process into two layers: high-level instructions and low-level actions.
Outcome: The proposed method reduces the forgetting of old tasks compared to other methods, while orthogonally training the remaining parts.

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