American Psychological Association 6th edition

Shang, X., Fu, Z., Cheng, S., Chen, G., Li, G., Hu, L., Zhang, W., & Yu, N. (2026). An empirical study on the effectiveness of large language models for binary code understanding. Empirical Software Engineering: An International Journal, 31(1). https://doi.org/10.1007/s10664-025-10748-5

ISO-690 (author-date, English)

SHANG, Xiuwei, FU, Zhenkan, CHENG, Shaoyin, CHEN, Guoqiang, LI, Gangyang, HU, Li, ZHANG, Weiming and YU, Nenghai, 2026. An empirical study on the effectiveness of large language models for binary code understanding. Empirical Software Engineering: An International Journal. 1 February 2026. Vol. 31, no. 1, . DOI 10.1007/s10664-025-10748-5.

Modern Language Association 9th edition

Shang, X., Z. Fu, S. Cheng, G. Chen, G. Li, L. Hu, W. Zhang, and N. Yu. “An Empirical Study on the Effectiveness of Large Language Models for Binary Code Understanding”. Empirical Software Engineering: An International Journal, vol. 31, no. 1, Feb. 2026, https://doi.org/10.1007/s10664-025-10748-5.

Mohr Siebeck - Recht (Deutsch - Österreich)

Shang, Xiuwei/Fu, Zhenkan/Cheng, Shaoyin/Chen, Guoqiang/Li, Gangyang/Hu, Li et al.: An empirical study on the effectiveness of large language models for binary code understanding, Empirical Software Engineering: An International Journal 2026,

Emerald - Harvard

Shang, X., Fu, Z., Cheng, S., Chen, G., Li, G., Hu, L., Zhang, W. and Yu, N. (2026), “An empirical study on the effectiveness of large language models for binary code understanding”, Empirical Software Engineering: An International Journal, Vol. 31 No. 1, available at:https://doi.org/10.1007/s10664-025-10748-5.

Warning: These citations may not always be 100% accurate.