Papers by Saier Hu

1 papers
Large Language Models Badly Generalize across Option Length, Problem Types, and Irrelevant Noun Replacements (2025.emnlp-main)

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Challenge: Existing benchmarks have exposed patterns and may not truly assess generalization ability of Large Language Models (LLMs).
Approach: They propose a “Generalization Stress Test” to assess Large Language Models’ generalization ability under slight and controlled perturbations, including option length, problem types, and irrelevant noun replacements.
Outcome: The proposed test shows that LLMs exhibit severe accuracy drops and unexpected biases when faced with minor but content-preserving modifications.

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