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SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
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Cites
SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents
Mündler, N., Müller, M., He, J., & Vechev, M. (2024) · Advances in Neural Information Processing Systems 37 · doi:10.52202/079017-2601 · Cited by 25
CodeR: Issue Resolving with Multi-Agent and Task Graphs
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Self-citation
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Cited by
Free-MAD: Consensus-Free Multi-Agent Debate
Cui, Y., Fu, H., Zhang, H., Wang, L., & Zuo, C. (2026) · Findings of the Association for Computational Linguistics: ACL 2026 · doi:10.18653/v1/2026.findings-acl.1600 · Cited by 28
LongCodeZip: Compress Long Context for Code Language Models
Shi, Y., Qian, Y., Zhang, H., Shen, B., & Gu, X. (2025) · 2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE) · doi:10.1109/ase63991.2025.00020 · Cited by 7
Self-citationSWE-Pruner: Self-Adaptive Context Pruning for Coding Agents
Wang, Y., Shi, Y., Yang, M., Zhang, R., He, S., Lian, H., Chen, Y., Ye, S., Cai, K., & Gu, X. (2026) · arXiv · doi:10.48550/arxiv.2601.16746 · Cited by 2
“…in software engineering tasks, from simple code understanding (Chen et al., 2021; Li et al., 2023b; Yang et al., 2025; Hu et al., 2025) to interactive agents capable of navigating repositories, running tests, and submitting patches end-to-end (Chen et al., 2025; Li et al., 2025; Xiao et al., 2025).”
Self-citationLongCodeZip: Compress Long Context for Code Language Models
Shi, Y., Qian, Y., Zhang, H., Shen, B., & Gu, X. (2025) · arXiv · Cited by 7
“LLMs specialized for code have revolutionized software development by demonstrating remarkable capabilities in code completion [1], [2], translation [3], [4], program synthesis [5], [6], [7] and program repair [8], [9].”
Self-citationMulti-agent Collaboration with State Management
Liu, M., Chen, T., Xu, Z., Jiang, X., & Dong, Y. (2026) · arXiv
Metadata
- Authors
- Li, H., Shi, Y., Lin, S., Gu, X., Lian, H., Wang, X., Jia, Y., Huang, T., & Wang, Q.
- Venue
- Proceedings of the 2026 IEEE/ACM 48th International Conference on Software Engineering
- Publisher
- ACM
- Published
- 2026-04-12
- Pages
- 1380-1392
- Cited by
- 2
- References
- 2
- Funders
- The National Key Research and Development Program of China (2023YFB4503802)
- The Natural Science Foundation of Shanghai (25ZR1401175)
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- Li, H., Shi, Y., Lin, S., Gu, X., Lian, H., Wang, X., Jia, Y., Huang, T., & Wang, Q. (2026). SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution. Proceedings of the 2026 IEEE/ACM 48th International Conference on Software Engineering. https://doi.org/10.1145/3744916.3787810
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.