3 papers
cs.LG2026
Personalized Group Relative Policy Optimization for Heterogenous Preference Alignment
Jialu Wang, Heinrich Peters, Asad A. Butt +6
Despite their sophisticated general-purpose capabilities, Large Language Models (LLMs) often fail to align with diverse individual preferences because standard post-training method…
cs.LG2023
Generalizable Error Modeling for Human Data Annotation: Evidence From an Industry-Scale Search Data Annotation Program
Heinrich Peters, Alireza Hashemi, James Rae
Machine learning (ML) and artificial intelligence (AI) systems rely heavily on human-annotated data for training and evaluation. A major challenge in this context is the occurrence…
cs.SE2023
Model Share AI: An Integrated Toolkit for Collaborative Machine Learning Model Development, Provenance Tracking, and Deployment in Python
Heinrich Peters, Michael Parrott
Machine learning (ML) has the potential to revolutionize a wide range of research areas and industries, but many ML projects never progress past the proof-of-concept stage. To addr…