3 papers
stat.ML2026
Unsupervised Identification and Removal of Spurious Correlations During Fine-Tuning
Ciarán M. Gilligan-Lee, Joseph Egan, Yuchen Zhu +1
Fine-tuning a pretrained language model on a curated dataset can produce spurious correlations between the fine-tuning task and unintended latent factors -- such as misaligned pers…
stat.ME2025
Local Interference: Removing Interference Bias in Semi-Parametric Causal Models
Michael O'Riordan, Ciarán M. Gilligan-Lee
Interference bias is a major impediment to identifying causal effects in real-world settings. For example, vaccination reduces the transmission of a virus in a population such that…
stat.ME2024
Spillover Detection for Donor Selection in Synthetic Control Models
Michael O'Riordan, Ciarán M. Gilligan-Lee
Synthetic control (SC) models are widely used to estimate causal effects in settings with observational time-series data. To identify the causal effect on a target unit, SC require…