2025
Likelihood Variance as Text Importance for Resampling Texts to Map Language Models
EMNLP 2025
We address the computational cost of constructing a model map, which embeds diverse language models into a common space for comparison via KL divergence. The map relies on log-likelihoods over a large text set, making the cost proportional to the number of texts. To reduce this cost, we propose a re