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Analyzing Memory Effects in Large Language Models through the Lens of Cognitive Psychology

Interdisciplinary Studies

Analyzing Memory Effects in Large Language Models through the Lens of Cognitive Psychology

Z. Cao, L. Schooler, et al.

Memory is adaptive but fallible — and this study finds that cutting-edge language models echo many human memory quirks. Using classic human-memory paradigms, the authors show LLMs display list-length and list-strength effects, associative interference, DRM-style false recognitions, and cross-domain generalization, while differing in order sensitivity and resilience to nonsense. This research was conducted by Zhaoyang Cao, Lael Schooler, and Reza Zafarani.

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