Papers with scalable weak-to-strong episodic learning framework

1 papers
Growing Through Experience: Scaling Episodic Grounding in Language Models (2025.acl-long)

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Challenge: Language models (LMs) require effective episodic grounding to perform well at physical planning tasks due to their limited ability to learn from and apply past experiences.
Approach: They propose a weak-to-strong episodic learning framework that integrates episodic memory into hierarchical representations and pre-trained knowledge to unlock larger LMs' potential for grounding.
Outcome: The proposed framework outperforms top proprietary LMs by 3.45% across diverse planning and question-answering tasks.

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