Agent-based AI workflows repair injected reproducibility failures in R social-science code at 69-96% success, substantially outperforming prompt-based LLM approaches at 31-79%.
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SFT followed by RLVR on Qwen2.5-3B-Instruct raises syntactic and execution correctness when generating Game Code World Models across 30 games.
citing papers explorer
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Automating Computational Reproducibility in Social Science: Comparing Prompt-Based and Agent-Based Approaches
Agent-based AI workflows repair injected reproducibility failures in R social-science code at 69-96% success, substantially outperforming prompt-based LLM approaches at 31-79%.
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Distilling Game Code World Model Generation into Lightweight Large Language Models
SFT followed by RLVR on Qwen2.5-3B-Instruct raises syntactic and execution correctness when generating Game Code World Models across 30 games.