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This work proposes a method that generates computationally sound solutions with dependency graphs for execution-consistent preference optimization, and achieves 50.1% accuracy on PhyX multimodal physics reasoning, surpassing DeepSeek-R1 and OpenAI o3-mini.
CompileRover employs a sophisticated three-role collaboration mechanism, comprising a referee, an advisor, and an operator, effectively overcoming performance bottlenecks by leveraging comprehensive optimization algorithms and novel methodologies, including control flow analysis, code structure transformations, and dyn...
This work proposes a dependency-aware code generation framework that explicitly models interactions among code entities through a graph-based representation, and introduces a sparse triplet representation for strong dependencies, significantly improving storage efficiency and computational scalability.
P-SAPST Lite replaces peeling with a degree order and provides a lower latency order choice within the same framework and complements edge oblivious streaming APST by addressing an offline regime in which structural plans can be reused.
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