A framework with TOPPing source selection and VACAI-Bowl dual-branch model yields 54.62% average improvement in dependency parsing across 10 low-resource varieties.
Exploring alignment in shared cross-lingual spaces
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CL 2years
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The survey organizes mechanistic interpretability techniques into a Locate-Steer-Improve framework to enable actionable improvements in LLM alignment, capability, and efficiency.
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Harnessing Linguistic Dissimilarity for Language Generalization on Unseen Low-Resource Varieties
A framework with TOPPing source selection and VACAI-Bowl dual-branch model yields 54.62% average improvement in dependency parsing across 10 low-resource varieties.
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Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models
The survey organizes mechanistic interpretability techniques into a Locate-Steer-Improve framework to enable actionable improvements in LLM alignment, capability, and efficiency.