5 papers
Meta-Aligner: Bidirectional Preference-Policy Optimization for Multi-Objective LLMs Alignment
Wenzhe Xu, Biao Liu, Yiyang Sun +2
Multi-Objective Alignment aims to align Large Language Models (LLMs) with diverse and often conflicting human values by optimizing multiple objectives simultaneously. Existing meth…
The Rashomon Effect for Visualizing High-Dimensional Data
Yiyang Sun, Haiyang Huang, Gaurav Rajesh Parikh +1
Dimension reduction (DR) is inherently non-unique: multiple embeddings can preserve the structure of high-dimensional data equally well while differing in layout or geometry. In th…
Dimension Reduction with Locally Adjusted Graphs
Yingfan Wang, Yiyang Sun, Haiyang Huang +1
Dimension reduction (DR) algorithms have proven to be extremely useful for gaining insight into large-scale high-dimensional datasets, particularly finding clusters in transcriptom…
Improving Decision Sparsity
Yiyang Sun, Tong Wang, Cynthia Rudin
Sparsity is a central aspect of interpretability in machine learning. Typically, sparsity is measured in terms of the size of a model globally, such as the number of variables it u…
Sparse and Faithful Explanations Without Sparse Models
Yiyang Sun, Zhi Chen, Vittorio Orlandi +2
Even if a model is not globally sparse, it is possible for decisions made from that model to be accurately and faithfully described by a small number of features. For instance, an…