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Shiguang Guo

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
2024

Open Grounded Planning: Challenges and Benchmark Construction

ACL 2024long

The emergence of large language models (LLMs) has increasingly drawn attention to the use of LLMs for human-like planning. Existing work on LLM-based planning either focuses on leveraging the inherent language generation capabilities of LLMs to produce free-style plans, or employs reinforcement lear…