{"id":63243,"date":"2025-04-14T20:34:05","date_gmt":"2025-04-14T20:34:05","guid":{"rendered":""},"modified":"2025-04-14T20:34:05","modified_gmt":"2025-04-14T20:34:05","slug":"%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-63243","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-63243\/","title":{"rendered":"\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u0646\u0648\u0639 \u0647\u0648\u0634 \u0631\u0627 \u062a\u0642\u0648\u06cc\u062a \u0645\u06cc \u06a9\u0646\u062f: \u06cc\u06a9\u067e\u0627\u0631\u0686\u0647 \u0633\u0627\u0632\u06cc \u062a\u062e\u0635\u0635 \u0639\u0648\u0627\u0645\u0644 \u0645\u0647\u0646\u062f\u0633\u06cc \u0646\u0631\u0645 \u0627\u0641\u0632\u0627\u0631"},"content":{"rendered":"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nDiversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents<\/td>\n<\/tr>\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u062a\u0646\u0648\u0639 \u0647\u0648\u0634 \u0631\u0627 \u062a\u0642\u0648\u06cc\u062a \u0645\u06cc \u06a9\u0646\u062f: \u06cc\u06a9\u067e\u0627\u0631\u0686\u0647 \u0633\u0627\u0632\u06cc \u062a\u062e\u0635\u0635 \u0639\u0648\u0627\u0645\u0644 \u0645\u0647\u0646\u062f\u0633\u06cc \u0646\u0631\u0645 \u0627\u0641\u0632\u0627\u0631<\/td>\n<\/tr>\n
\u0646\u0648\u06cc\u0633\u0646\u062f\u06af\u0627\u0646 <\/td>\nKexun Zhang, Weiran Yao, Zuxin Liu, Yihao Feng, Zhiwei Liu, Rithesh Murthy, Tian Lan, Lei Li, Renze Lou, Jiacheng Xu, Bo Pang, Yingbo Zhou, Shelby Heinecke, Silvio Savarese, Huan Wang, Caiming Xiong<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nPDF<\/td>\n<\/tr>\n
\u0632\u0628\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u062a\u062d\u0648\u06cc\u0644\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u062a\u0631\u062c\u0645\u0647 \u0634\u062f\u0647 <\/td>\n\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\n<\/tr>\n
\u0646\u062d\u0648\u0647 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 <\/td>\n\u062f\u0648 \u062a\u0627 \u0633\u0647 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634 (\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u062f\u0627\u0646\u0644\u0648\u062f\u06cc)<\/td>\n<\/tr>\n
\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a<\/td>\n13<\/td>\n<\/tr>\n
\u0644\u06cc\u0646\u06a9 \u062f\u0627\u0646\u0644\u0648\u062f \u0631\u0627\u06cc\u06af\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/td>\n\u062f\u0627\u0646\u0644\u0648\u062f \u0645\u0642\u0627\u0644\u0647<\/a><\/td>\n<\/tr>\n
\u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0645\u0648\u0636\u0648\u0639\u0627\u062a <\/td>\nSoftware Engineering,Artificial Intelligence,Computation and Language,Machine Learning,\u0645\u0647\u0646\u062f\u0633\u06cc \u0646\u0631\u0645 \u0627\u0641\u0632\u0627\u0631 , \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc , \u0645\u062d\u0627\u0633\u0628\u0627\u062a \u0648 \u0632\u0628\u0627\u0646 , \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 ,<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a <\/td>\nSubmitted 13 August, 2024; originally announced August 2024.<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u0627\u0631\u0633\u0627\u0644 \u0634\u062f\u0647 \u062f\u0631 13 \u0627\u0648\u062a 2024 \u061b\u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u0627\u0648\u062a 2024 \u0627\u0639\u0644\u0627\u0645 \u0634\u062f.<\/td>\n<\/tr>\n
\u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0628\u06cc\u0634\u062a\u0631 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u062f\u0631 \u067e\u0627\u06cc\u06af\u0627\u0647 \u0647\u0627\u06cc \u0639\u0644\u0645\u06cc <\/td>\n\n INSPIRE HEP<\/a>
\n
\n NASA ADS<\/a>
\n
\n Google Scholar<\/a>
\n
\n Semantic Scholar<\/a>
\n
\n arXiv<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n

\u0686\u06a9\u06cc\u062f\u0647<\/h2>\n

Large language model (LLM) agents have shown great potential in solving real-world software engineering (SWE) problems. The most advanced open-source SWE agent can resolve over 27% of real GitHub issues in SWE-Bench Lite. However, these sophisticated agent frameworks exhibit varying strengths, excelling in certain tasks while underperforming in others. To fully harness the diversity of these agents, we propose DEI (Diversity Empowered Intelligence), a framework that leverages their unique expertise. DEI functions as a meta-module atop existing SWE agent frameworks, managing agent collectives for enhanced problem-solving. Experimental results show that a DEI-guided committee of agents is able to surpass the best individual agent’s performance by a large margin. For instance, a group of open-source SWE agents, with a maximum individual resolve rate of 27.3% on SWE-Bench Lite, can achieve a 34.3% resolve rate with DEI, making a 25% improvement and beating most closed-source solutions. Our best-performing group excels with a 55% resolve rate, securing the highest ranking on SWE-Bench Lite. Our findings contribute to the growing body of research on collaborative AI systems and their potential to solve complex software engineering challenges.<\/p>\n

\u0686\u06a9\u06cc\u062f\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc (\u062a\u0631\u062c\u0645\u0647 \u0645\u0627\u0634\u06cc\u0646\u06cc)<\/h2>\n

\u0639\u0648\u0627\u0645\u0644 \u0645\u062f\u0644 \u0628\u0632\u0631\u06af \u0632\u0628\u0627\u0646 (LLM) \u067e\u062a\u0627\u0646\u0633\u06cc\u0644 \u0632\u06cc\u0627\u062f\u06cc \u062f\u0631 \u062d\u0644 \u0645\u0634\u06a9\u0644\u0627\u062a \u0645\u0647\u0646\u062f\u0633\u06cc \u0646\u0631\u0645 \u0627\u0641\u0632\u0627\u0631 \u062f\u0631 \u062f\u0646\u06cc\u0627\u06cc \u0648\u0627\u0642\u0639\u06cc (SWE) \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0647 \u0627\u0646\u062f.\u067e\u06cc\u0634\u0631\u0641\u062a\u0647 \u062a\u0631\u06cc\u0646 \u0639\u0627\u0645\u0644 \u0645\u0646\u0628\u0639 \u0628\u0627\u0632 SWE \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u06cc\u0634 \u0627\u0632 27 \u066a \u0627\u0632 \u0645\u0648\u0636\u0648\u0639\u0627\u062a \u0648\u0627\u0642\u0639\u06cc GitHub \u0631\u0627 \u062f\u0631 SWE-Bench Lite \u062d\u0644 \u06a9\u0646\u062f.\u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644 \u060c \u0627\u06cc\u0646 \u0686\u0627\u0631\u0686\u0648\u0628 \u0647\u0627\u06cc \u0639\u0627\u0645\u0644 \u067e\u06cc\u0634\u0631\u0641\u062a\u0647 \u0646\u0642\u0627\u0637 \u0642\u0648\u062a \u0645\u062e\u062a\u0644\u0641\u06cc \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u0646\u062f \u060c \u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647 \u062f\u0631 \u062f\u06cc\u06af\u0631\u0627\u0646 \u06a9\u0645 \u062a\u062d\u0631\u06a9 \u0627\u0633\u062a \u060c \u062f\u0631 \u0628\u0631\u062e\u06cc \u06a9\u0627\u0631\u0647\u0627 \u0639\u0627\u0644\u06cc \u0627\u0633\u062a.\u0628\u0631\u0627\u06cc \u0645\u0647\u0627\u0631 \u06a9\u0627\u0645\u0644 \u062a\u0646\u0648\u0639 \u0627\u06cc\u0646 \u0639\u0648\u0627\u0645\u0644 \u060c \u0645\u0627 DEI (\u062a\u0646\u0648\u0639 \u0647\u0648\u0634 \u062a\u0648\u0627\u0646\u0645\u0646\u062f) \u0631\u0627 \u067e\u06cc\u0634\u0646\u0647\u0627\u062f \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u060c \u0686\u0627\u0631\u0686\u0648\u0628\u06cc \u06a9\u0647 \u0627\u0632 \u062a\u062e\u0635\u0635 \u0645\u0646\u062d\u0635\u0631 \u0628\u0647 \u0641\u0631\u062f \u0622\u0646\u0647\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f.DEI \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u06cc\u06a9 \u0645\u0627\u0698\u0648\u0644 \u0645\u062a\u0627 \u062f\u0631 \u0628\u0627\u0644\u0627\u06cc \u0686\u0627\u0631\u0686\u0648\u0628 \u0647\u0627\u06cc \u0639\u0627\u0645\u0644 SWE \u0645\u0648\u062c\u0648\u062f \u060c \u0645\u062f\u06cc\u0631\u06cc\u062a \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0645\u062f\u06cc\u0631\u06cc\u062a \u062c\u0645\u0639 \u0622\u0648\u0631\u06cc \u0645\u0634\u06a9\u0644 \u0628\u0631\u0627\u06cc \u062d\u0644 \u0645\u0633\u0626\u0644\u0647 \u0631\u0627 \u0627\u0641\u0632\u0627\u06cc\u0634 \u0645\u06cc \u062f\u0647\u062f.\u0646\u062a\u0627\u06cc\u062c \u062a\u062c\u0631\u0628\u06cc \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 \u06cc\u06a9 \u06a9\u0645\u06cc\u062a\u0647 \u0628\u0627 \u0647\u062f\u0627\u06cc\u062a \u062f\u06cc \u0628\u0627 \u0647\u062f\u0627\u06cc\u062a \u0642\u0627\u062f\u0631 \u0628\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f \u0628\u0647\u062a\u0631\u06cc\u0646 \u0639\u0627\u0645\u0644 \u0641\u0631\u062f\u06cc \u0628\u0627 \u062d\u0627\u0634\u06cc\u0647 \u0628\u0632\u0631\u06af\u06cc \u0627\u0633\u062a.\u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644 \u060c \u06af\u0631\u0648\u0647\u06cc \u0627\u0632 \u0639\u0648\u0627\u0645\u0644 SWE \u0628\u0627 \u0645\u0646\u0628\u0639 \u0628\u0627\u0632 \u060c \u0628\u0627 \u062d\u062f\u0627\u06a9\u062b\u0631 \u0645\u06cc\u0632\u0627\u0646 \u062d\u0644 \u0648 \u0641\u0635\u0644 \u0641\u0631\u062f\u06cc 27.3 \u066a \u062f\u0631 SWE-Bench Lite \u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u0646\u062f \u0628\u0627 DEI \u0628\u0647 \u0645\u06cc\u0632\u0627\u0646 34.3 \u066a \u062d\u0644 \u0648 \u0641\u0635\u0644 \u062f\u0633\u062a \u06cc\u0627\u0628\u0646\u062f \u0648 \u0628\u0627\u0639\u062b \u0628\u0647\u0628\u0648\u062f 25 \u066a \u0648 \u0636\u0631\u0628 \u0648 \u0634\u062a\u0645 \u0628\u06cc\u0634\u062a\u0631 \u0631\u0627\u0647 \u062d\u0644 \u0647\u0627\u06cc \u0645\u0646\u0628\u0639 \u0628\u0633\u062a\u0647 \u0645\u06cc \u0634\u0648\u0646\u062f.\u06af\u0631\u0648\u0647 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u0627 \u0628\u0627 55 \u066a Resolve \u0628\u0631\u062a\u0631\u06cc \u062f\u0627\u0631\u062f \u0648 \u0628\u0627\u0644\u0627\u062a\u0631\u06cc\u0646 \u0631\u062a\u0628\u0647 \u0631\u0627 \u062f\u0631 SWE-BENCH LITE \u062a\u0636\u0645\u06cc\u0646 \u0645\u06cc \u06a9\u0646\u062f.\u06cc\u0627\u0641\u062a\u0647 \u0647\u0627\u06cc \u0645\u0627 \u0628\u0647 \u0631\u0634\u062f \u0628\u062f\u0646\u0647 \u062a\u062d\u0642\u06cc\u0642 \u062f\u0631 \u0645\u0648\u0631\u062f \u0633\u06cc\u0633\u062a\u0645 \u0647\u0627\u06cc \u0645\u0634\u062a\u0631\u06a9 \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u0648 \u067e\u062a\u0627\u0646\u0633\u06cc\u0644 \u0622\u0646\u0647\u0627 \u0628\u0631\u0627\u06cc \u062d\u0644 \u0686\u0627\u0644\u0634 \u0647\u0627\u06cc \u067e\u06cc\u0686\u06cc\u062f\u0647 \u0645\u0647\u0646\u062f\u0633\u06cc \u0646\u0631\u0645 \u0627\u0641\u0632\u0627\u0631 \u06a9\u0645\u06a9 \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
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