36 citations · 48 across the 11 of their papers we have counts for
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cs.AI2026
From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models
Ling Shi, Xinwei Wu, Xiaohu Zhao +7
While mechanistic interpretability tools like Sparse Autoencoders (SAEs) can uncover meaningful features within Large Language Models (LLMs), a critical gap remains in transforming…
cs.CL2026
Finding the Translation Switch: Discovering and Exploiting the Task-Initiation Features in LLMs
Xinwei Wu, Heng Liu, Xiaohu Zhao +6
Large Language Models (LLMs) frequently exhibit strong translation abilities, even without task-specific fine-tuning. However, the internal mechanisms governing this innate capabil…