5 papers
SPECTRA: Revealing the Full Spectrum of User Preferences via Distributional LLM Inference
Luyang Zhang, Jialu Wang, Shichao Zhu +4
Large Language Models (LLMs) are increasingly used to model user preferences, with the typical output as a directly-generated ranked item list per user. However, this generative pa…
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…
InfiMed: Low-Resource Medical MLLMs with Advancing Understanding and Reasoning
Zeyu Liu, Zhitian Hou, Guanghao Zhu +3
Multimodal Large Language Models (MLLMs) have achieved remarkable progress in domains such as visual understanding and mathematical reasoning. However, their application in the med…
Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges
Usman Gohar, Zeyu Tang, Jialu Wang +4
The widespread integration of Machine Learning systems in daily life, particularly in high-stakes domains, has raised concerns about the fairness implications. While prior works ha…
Fairness Without Harm: An Influence-Guided Active Sampling Approach
Jinlong Pang, Jialu Wang, Zhaowei Zhu +3
The pursuit of fairness in machine learning (ML), ensuring that the models do not exhibit biases toward protected demographic groups, typically results in a compromise scenario. Th…