Antonios Georgiou

The paper introduces a random tree model to explain quantitative features of narrative recall, showing sublinear recall length growth and scale-invariant summary distributions.

The paper uses large language models to design memory experiments and analyze human recall and recognition of narratives, finding linear scaling with length and preserved recognition in scrambled narratives.

The paper examines how forgetting dynamics vary across different materials and finds that curves fall on a discrete spectrum, compatible with a model based on retrograde interference.

The paper introduces a phenomenological model of forgetting based on retroactive interference, showing that older memories are more stable than newer ones through recognition experiments.