Two new benchmarks, SWE-Together and SWE-Interact, have been introduced to evaluate coding agents in more realistic, interactive, and multi-turn user sessions. Unlike static benchmarks that provide complete task descriptions upfront, these new frameworks simulate user interactions, progressively revealing requirements, and providing feedback. Experiments show that strong performance on single-turn tasks does not always translate to multi-turn scenarios, with top models like Opus 4.8 and GPT 5.5 still exhibiting issues like forgetting requirements or making technical mistakes. AI
IMPACT These benchmarks will drive development of more capable AI coding assistants that can handle complex, interactive software engineering tasks.
RANK_REASON Two academic papers introduce new benchmarks for evaluating AI coding agents.
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- alphaXiv
- arXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- GPT 5.5
- Hugging Face
- Opus 4.8
- ScienceCast
- SWE-Interact
- SWE-Together
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