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Alex Zhuang

2 accepted papers

2024

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

NeurIPS 2024spotlight

In the age of large-scale language models, benchmarks like the Massive Multitask Language Understanding (MMLU) have been pivotal in pushing the boundaries of what AI can achieve in language comprehension and reasoning across diverse domains. However, as models continue to improve, their performance…

Cited by 269SourcePDFScholar
2023

Few-shot In-context Learning on Knowledge Base Question Answering

ACL 2023long

Question answering over knowledge bases is considered a difficult problem due to the challenge of generalizing to a wide variety of possible natural language questions. Additionally, the heterogeneity of knowledge base schema items between different knowledge bases often necessitates specialized tra…