Papers with MzsRE

2 papers
Retrieval-Augmented Multilingual Knowledge Editing (2024.acl-long)

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Challenge: Knowledge editing (KE) is an effective and economical alternative to inject new knowledge or to fix factual errors in Large Language Models (LLMs).
Approach: They propose a multilingual knowledge editing method that can be used to update knowledge in LLMs by concatenating new knowledge retrieved from a knowledge base with users’ prompts before querying an LLM.
Outcome: The proposed method outperforms baseline knowledge editing methods by a significant margin and is scalable to real-word application scenarios.
CLICKER: Cross-Lingual Knowledge Editing via In-Context Learning with Adaptive Stepwise Reasoning (2026.findings-eacl)

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Challenge: Existing knowledge editing methods are static and fail to propagate edits across languages.
Approach: They propose a KE method that dynamically retrieves only knowledge relevant to a given query and edits it to maintain cross-lingual consistency.
Outcome: The proposed method outperforms static KE methods on a multilingual dataset with semantically similar but irrelevant prompts.

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