3 papers
cs.LG2026
What do Reward Models Memorize?
Ivo Verhoeven, Pushkar Mishra, Ekaterina Shutova
This paper studies what discriminatively trained reward models (RMs) memorize by measuring counterfactual memorization on two human preference datasets. We show that RMs 1) misallo…
cs.IR2025
Yesterday's News: Benchmarking Multi-Dimensional Out-of-Distribution Generalization of Misinformation Detection Models
Ivo Verhoeven, Pushkar Mishra, Ekaterina Shutova
This article introduces misinfo-general, a benchmark dataset for evaluating misinformation models' ability to perform out-of-distribution generalization. Misinformation changes rap…
cs.LG2025
ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective
Yihong Chen, Pushkar Mishra, Luca Franceschi +3
Factorisation-based Models (FMs), such as DistMult, have enjoyed enduring success for Knowledge Graph Completion (KGC) tasks, often outperforming Graph Neural Networks (GNNs). Howe…