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Xuemin Yu

2 accepted papers

2024

Latent Concept-based Explanation of NLP Models

EMNLP 2024main

Interpreting and understanding the predictions made by deep learning models poses a formidable challenge due to their inherently opaque nature. Many previous efforts aimed at explaining these predictions rely on input features, specifically, the words within NLP models. However, such explanations ar…

2024

Long-form evaluation of model editing

NAACL 2024long

Evaluations of model editing, a technique for changing the factual knowledge held by Large Language Models (LLMs), currently only use the ‘next few token’ completions after a prompt. As a result, the impact of these methods on longer natural language generation is largely unknown. We introduce long-…