Brief

A new paper published on arXiv proposes a framework for evaluating foundation model research, treating it as a causal inference problem. The authors argue that the high cost of controlled experiments with large models necessitates the use of cost-saving strategies like proxy experiments, scaling laws, and observational studies. However, these methods introduce validity threats that can undermine research claims. The proposed framework assesses these strategies based on statistical, internal, external, and construct validity, highlighting the trade-offs inherent in each approach. AI