5 papers
QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs
Santiago Gonzalez, Alireza Amiri Bavandpour, Peter Ye +48
As Large Language Models (LLMs) saturate elementary benchmarks, the research frontier has shifted from generation to the reliability of automated evaluation. We demonstrate that st…
Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression
Dimitri Meunier, Jakub Wornbard, Vladimir R. Kostic +5
We address the problem of causal effect estimation in the presence of hidden confounders using nonparametric instrumental variable (IV) regression. An established approach is to us…
When Lower-Order Terms Dominate: Adaptive Expert Algorithms for Heavy-Tailed Losses
Antoine Moulin, Emmanuel Esposito, Dirk van der Hoeven
We consider the problem setting of prediction with expert advice with possibly heavy-tailed losses, i.e. the only assumption on the losses is an upper bound on their second moments…
Demystifying Spectral Feature Learning for Instrumental Variable Regression
Dimitri Meunier, Antoine Moulin, Jakub Wornbard +2
We address the problem of causal effect estimation in the presence of hidden confounders, using nonparametric instrumental variable (IV) regression. A leading strategy employs spec…
Spectral Representation for Causal Estimation with Hidden Confounders
Haotian Sun, Antoine Moulin, Tongzheng Ren +2
We address the problem of causal effect estimation where hidden confounders are present, with a focus on two settings: instrumental variable regression with additional observed con…