2 citations · 4 across the 5 of their papers we have counts for
5 papers
Temporal Context Reinstatement Drives Episodic-Like Order Memory in Long-Context Language Models
Mathis Pink, Vy Ai Vo, Qinyuan Wu +7
Human episodic memory supports the retrieval of experiences that unfold over extended timescales, yet the computational mechanisms underlying this ability remain debated due to the…
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…
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…
Assessing Episodic Memory in LLMs with Sequence Order Recall Tasks
Mathis Pink, Vy A. Vo, Qinyuan Wu +7
Current LLM benchmarks focus on evaluating models' memory of facts and semantic relations, primarily assessing semantic aspects of long-term memory. However, in humans, long-term m…
Humans and language models diverge when predicting repeating text
Aditya R. Vaidya, Javier Turek, Alexander G. Huth
Language models that are trained on the next-word prediction task have been shown to accurately model human behavior in word prediction and reading speed. In contrast with these fi…