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20222026
most citedTowards Understanding What Code Language Models Learned

3 citations · 6 across the 5 of their papers we have counts for

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cs.SE2025

EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention

Yifan Zhang, Chen Huang, Yueke Zhang +5

Code Language Models (CodeLLMs) learn token importance from data correlations, whereas human developers attend selectively to semantically salient code. We present EyeMulator, a mo…

cs.SE2025★ 2 cited

Enhancing Code LLM Training with Programmer Attention

Yifan Zhang, Chen Huang, Zachary Karas +3

Human attention provides valuable yet underexploited signals for code LLM training, offering a perspective beyond purely machine-driven attention. Despite the complexity and cost o…