19 citations · 27 across the 9 of their papers we have counts for
3 papers · 1 filter
AI Cartography: Mapping the Latent Landscape of AI Benchmark Ecosystems
Michael Hardy, Anka Reuel, Lijin Zhang +6
While aggregate leaderboard scores drive AI development, they contain substantial measurement noise whose sources and magnitudes remain unquantified, making it unclear when ranking…
Understanding Student Effort Using Response-Time Propensities During Problem Solving
Conrad Borchers, Lijin Zhang, Kexin Yang +2
Adaptive learning systems can produce substantial learning gains, yet many students engage for too brief or too superficial a period to benefit. A central obstacle is measuring eff…
Efficient Detection of Bad Benchmark Items with Novel Scalability Coefficients
Michael Hardy, Joshua Gilbert, Benjamin Domingue
The validity of assessments, from large-scale AI benchmarks to human classrooms, depends on the quality of individual items, yet modern evaluation instruments often contain thousan…