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pro vyhledávání: '"Zeng, Weiliang Will"'
The emergence of large language models (LLMs) has significantly pushed the frontiers of program synthesis. Advancement of LLM-based program synthesis calls for a thorough evaluation of LLM-generated code. Most evaluation frameworks focus on the (func
Externí odkaz:
http://arxiv.org/abs/2406.06647
Autor:
Gagrani, Mukul, Rainone, Corrado, Yang, Yang, Teague, Harris, Jeon, Wonseok, Van Hoof, Herke, Zeng, Weiliang Will, Zappi, Piero, Lott, Christopher, Bondesan, Roberto
Recent works on machine learning for combinatorial optimization have shown that learning based approaches can outperform heuristic methods in terms of speed and performance. In this paper, we consider the problem of finding an optimal topological ord
Externí odkaz:
http://arxiv.org/abs/2207.05899