ARIADNE combines blackboard architecture with MCTS to coordinate strategy, code, test, evaluation, and repair stages, yielding higher Pass@1 scores than prior LLM baselines on APPS, CodeContests, and related benchmarks.
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A review of 114 studies creates taxonomies for code and data quality issues, formalizes 18 propagation mechanisms from training data defects to LLM-generated code defects, and synthesizes detection and mitigation techniques.
Develops a conceptual distinction between human-cognitive and artificial-stochastic error architectures in code generation, drawing on Dennett, Rescher, and Floridi to explore implications for AI-human collaboration.
citing papers explorer
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ARIADNE: Agentic Reward-Informed Adaptive Decision Exploration via Blackboard-Driven MCTS for Competitive Program Generation
ARIADNE combines blackboard architecture with MCTS to coordinate strategy, code, test, evaluation, and repair stages, yielding higher Pass@1 scores than prior LLM baselines on APPS, CodeContests, and related benchmarks.
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Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code
A review of 114 studies creates taxonomies for code and data quality issues, formalizes 18 propagation mechanisms from training data defects to LLM-generated code defects, and synthesizes detection and mitigation techniques.
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Architectures of Error: A Philosophical Inquiry into AI and Human Code Generation
Develops a conceptual distinction between human-cognitive and artificial-stochastic error architectures in code generation, drawing on Dennett, Rescher, and Floridi to explore implications for AI-human collaboration.