Papers by Wenda Chu

1 papers
How Large Language Models Balance Internal Knowledge with User and Document Assertions (2026.findings-acl)

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Challenge: Large language models often need to balance their internal parametric knowledge with external information, such as user beliefs and content from retrieved documents, in real-world scenarios like RAG or chat-based systems.
Approach: They propose a three-source interaction framework to evaluate 27 large language models from 3 families on 2 datasets.
Outcome: The proposed framework systematically evaluates 27 large language models from 3 families on 2 datasets.

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