Multi Source Coding Problem Aggregation With Standardized Test Harnesses

via “multi-source dataset aggregation and standardization”

Visual mathematical reasoning benchmark.

Unique: Aggregates 28 existing datasets plus 3 new datasets into unified benchmark with standardized format, combining diverse sources to reduce bias from any single source. This aggregation approach is more comprehensive than single-source benchmarks but introduces complexity in managing source bias and ensuring consistent quality.

vs others: More comprehensive than single-source benchmarks because it combines diverse sources covering multiple visual-mathematical domains, reducing bias from any single dataset's annotation style or problem distribution.

via “multi-source coding problem aggregation with standardized test harnesses”

10K coding problems across 3 difficulty levels with test suites.

Unique: Combines problems from four independent online judge platforms with heterogeneous formats into a single normalized schema with consistent test execution semantics, rather than using a single-source benchmark like HumanEval or MBPP

vs others: 10x larger problem set than HumanEval (10K vs 164 problems) with higher algorithmic complexity and real-world difficulty distribution, making it more representative of production code generation challenges