4 citations · 4 across the 3 of their papers we have counts for
3 papers · 1 filter
Uncertainty-Normalized Margins for Direct Preference Optimization
Sadegh Khorasani, Petrus Mikkola, Matthias Grossglauser
Direct preference optimization (DPO) models binary preferences through a Bradley-Terry model with a common noise scale, without explicitly accounting for preference strength or pro…
Differentiable Structure Learning for Cyclic Linear Gaussian Models with Latent Confounders
Sadegh Khorasani, Ali Najar, Saber Salehkaleybar +1
We study causal structure learning from observational data in linear Gaussian structural causal models in the presence of directed cycles and an unknown number of exogenous latent…
Inference Time Causal Probing in LLMs
Sadegh Khorasani, Saber Salehkaleybar, Negar Kiyavash +1
Causal probing methods aim to test and control how internal representations influence the behavior of generative models. In causal probing, an intervention modifies hidden states s…