We evaluate universal self-consistency on a wide range of tasks, including mathematical rea-
soning, code generation, long-context summarization, and open-ended question answering. On
GSM8K (Cobbe et al., 2021) and MATH (Hendrycks et al., 2021) benchmarks for math problem
solving, USC generally matches the performance of the standard self-consistency. On programming
tasks including text-to-SQL generation (Li et al., 2023a) and Python code generation (Yin et al.,
2023), USC matches the performance of execution-based consistency (Li et al., 2022; Shi et al., 2022),
while USC does not require execution results to aggregate over candidate programs. Finally, USC
also improves the performance for open-ended question answering (Lin et al., 2021) and long-context
summarization (Huang et al., 2021; Chen et al., 2022b), where the standard self-consistency is not
applicable. In addition to the performance gain, our evaluation also demonstrates that USC outputs
UNIVERSALSELF-CONSISTENCYFORLARGELANGUAGEMODELGENERATION