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cs.LG2025
A Machine Learning Approach That Beats Large Rubik's Cubes
Alexander Chervov, Kirill Khoruzhii, Nikita Bukhal +9
The paper proposes a novel machine learning-based approach to the pathfinding problem on extremely large graphs. This method leverages diffusion distance estimation via a neural ne…
cs.LG2025★ 2 cited
Layer by Layer: Uncovering Hidden Representations in Language Models
Oscar Skean, Md Rifat Arefin, Dan Zhao +4
From extracting features to generating text, the outputs of large language models (LLMs) typically rely on the final layers, following the conventional wisdom that earlier layers c…