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cs.CL2025
Reversing Large Language Models for Efficient Training and Fine-Tuning
Eshed Gal, Moshe Eliasof, Javier Turek +3
Large Language Models (LLMs) are known for their expensive and time-consuming training. Thus, oftentimes, LLMs are fine-tuned to address a specific task, given the pretrained weigh…
cs.AI2025★ 1 cited
Position: Episodic Memory is the Missing Piece for Long-Term LLM Agents
Mathis Pink, Qinyuan Wu, Vy Ai Vo +4
As Large Language Models (LLMs) evolve from text-completion tools into fully fledged agents operating in dynamic environments, they must address the challenge of continually learni…