MAS-Algorithm is a multi-agent workflow that improves AI acceptance rates on algorithmic problems by 6.48% on average, outperforming parameter-efficient fine-tuning.
A survey on code generation with llm-based agents, 2025
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The paper organizes repository-level retrieval-augmented code generation into a unified framework covering retrieval substrate, control regime, and evaluation setting while summarizing strategies, datasets, and challenges.
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MAS-Algorithm: A Workflow for Solving Algorithmic Programming Problems with a Multi-Agent System
MAS-Algorithm is a multi-agent workflow that improves AI acceptance rates on algorithmic problems by 6.48% on average, outperforming parameter-efficient fine-tuning.
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Retrieval-Augmented Code Generation: A Survey with Focus on Repository-Level Approaches
The paper organizes repository-level retrieval-augmented code generation into a unified framework covering retrieval substrate, control regime, and evaluation setting while summarizing strategies, datasets, and challenges.