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cs.CL2025
Sparse Feature Coactivation Reveals Causal Semantic Modules in Large Language Models
Ruixuan Deng, Xiaoyang Hu, Miles Gilberti +5
We identify semantically coherent, context-consistent network components in large language models (LLMs) using coactivation of sparse autoencoder (SAE) features collected from just…
cs.CL2024
Do Language Models Understand the Cognitive Tasks Given to Them? Investigations with the N-Back Paradigm
Xiaoyang Hu, Richard L. Lewis
Cognitive tasks originally developed for humans are now increasingly used to study language models. While applying these tasks is often straightforward, interpreting their results…