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 editionShang, 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 - HarvardShang, 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.