7 citations · 12 across the 12 of their papers we have counts for
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cs.CL2024
Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers
Lorenzo Pacchiardi, Marko Tesic, Lucy G. Cheke +1
The integrity of AI benchmarks is fundamental to accurately assess the capabilities of AI systems. The internal validity of these benchmarks - i.e., making sure they are free from…
cs.CL2024★ 1 cited
100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances
Lorenzo Pacchiardi, Lucy G. Cheke, José Hernández-Orallo
Predicting the performance of LLMs on individual task instances is essential to ensure their reliability in high-stakes applications. To do so, a possibility is to evaluate the con…