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Should we really edit language models? on the evaluation of edited language models
Abstract Model editing has become an increasingly popular alternative for efficiently
updating knowledge within language models. Current methods mainly focus on reliability …
updating knowledge within language models. Current methods mainly focus on reliability …
Memla: Enhancing multilingual knowledge editing with neuron-masked low-rank adaptation
Knowledge editing aims to adjust the knowledge within large language models (LLMs) to
prevent their responses from becoming obsolete or inaccurate. However, existing works on …
prevent their responses from becoming obsolete or inaccurate. However, existing works on …
Knowledge localization: Mission not accomplished? enter query localization!
Large language models (LLMs) store extensive factual knowledge, but the mechanisms
behind how they store and express this knowledge remain unclear. The Knowledge Neuron …
behind how they store and express this knowledge remain unclear. The Knowledge Neuron …
Bring Your Own Knowledge: A Survey of Methods for LLM Knowledge Expansion
Adapting large language models (LLMs) to new and diverse knowledge is essential for their
lasting effectiveness in real-world applications. This survey provides an overview of state-of …
lasting effectiveness in real-world applications. This survey provides an overview of state-of …