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 und YU, Nenghai, 2026. An empirical study on the effectiveness of large language models for binary code understanding. Empirical Software Engineering: An International Journal. 1 Februar 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, und N. Yu. „An Empirical Study on the Effectiveness of Large Language Models for Binary Code Understanding“. Empirical Software Engineering: An International Journal, Bd. 31, Nr. 1, Februar 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 u. a.: 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. und 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, verfügbar unter:https://doi.org/10.1007/s10664-025-10748-5.