Preprint
Jul 2026
Explaining and Tuning Transformer-based LLMs in Arithmetic Tasks with Human Strategies
The findings reveal that transformer-based large language models exhibit learning patterns similar to those of human learners, with a faster learning speed for simpler subtasks compared to more complex ones, which suggests that transformer-based LLMs may share cognitive processes with human learners in arithmetic.
Luyu Qiu, Jianing Li, Hwanhee Kim et al.
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