Papers by Siqiao Huang

1 papers
Surge: On the Potential of Large Language Models as General-Purpose Surrogate Code Executors (2025.emnlp-main)

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Challenge: Neural surrogate models are powerful tools in data mining, but are underexplored . large language models (LLMs) have demonstrated remarkable capabilities in code-related tasks .
Approach: They propose a benchmarking framework to examine the feasibility of large language models . they examine scaling laws, data efficiency, and predictive accuracy of 21 open-source and proprietary LLMs .
Outcome: The proposed benchmark examines 21 open-source and proprietary LLMs . it also examines scaling laws, data efficiency, and predictive accuracy .

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