Maps common low-compute research strategies for foundation models onto statistical, internal, external, and construct validity threats via a causal-inference lens.
Zhihong Pan, Kai Zhang, Yuze Zhao, and Yupeng Han
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3representative citing papers
MCPP uses Monte Carlo simulations of workflow executions to dynamically allocate resources and replan, raising constrained completion probability over baselines on CodeFlow and ProofFlow.
Kernel ridge regression combined with mRMR feature selection improves prediction of full benchmark scores from question subsets over existing efficient benchmarking techniques.
citing papers explorer
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Validity Threats for Foundation Model Research
Maps common low-compute research strategies for foundation models onto statistical, internal, external, and construct validity threats via a causal-inference lens.
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On Time, Within Budget: Constraint-Driven Online Resource Allocation for Agentic Workflows
MCPP uses Monte Carlo simulations of workflow executions to dynamically allocate resources and replan, raising constrained completion probability over baselines on CodeFlow and ProofFlow.
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Efficient Benchmarking Is Just Feature Selection and Multiple Regression
Kernel ridge regression combined with mRMR feature selection improves prediction of full benchmark scores from question subsets over existing efficient benchmarking techniques.