RESEARCHarXiv CS.LG·4/14/2026
Human-like Working Memory Interference in Large Language Models
This study investigates working memory limitations in Large Language Models (LLMs), finding that they exhibit human-like interference signatures. Pretrained LLMs show performance degradation with increased memory load and bias by recency, even though transformers can be trained to perfectly solve such tasks.
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