89 citations · 455 across the 65 of their papers we have counts for
6 papers · 1 filter
A Latent Variable Framework for Scaling Laws in Large Language Models
Peiyao Cai, Chengyu Cui, Felipe Maia Polo +6
We propose a statistical framework built on latent variable modeling for scaling laws of large language models (LLMs). Our work is motivated by the rapid emergence of numerous new…
Bridging Human and LLM Judgments: Understanding and Narrowing the Gap
Felipe Maia Polo, Xinhe Wang, Mikhail Yurochkin +3
Large language models are increasingly used as judges (LLM-as-a-judge) to evaluate model outputs at scale, but their assessments often diverge systematically from human judgments.…
Identifiability and Inference for Generalized Latent Factor Models
Chengyu Cui, Gongjun Xu
Generalized latent factor analysis not only provides a useful latent embedding approach in statistics and machine learning, but also serves as a widely used tool across various sci…
Recurrent Event Analysis with Ordinary Differential Equations
Bo Meng, Weijing Tang, Gongjun Xu +1
This paper introduces a general framework for analyzing recurrent event data by modeling the conditional mean function of the recurrent event process as the solution to an Ordinary…
Accounting for Measurement Bias: A New Framework for Reliable Country Ranking in Large-Scale Educational Assessments
Jing Ouyang, Yunxiao Chen, Chengcheng Li +1
International Large-scale Assessments (ILSAs), such as the Program for International Student Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS)…
Denoising Diffused Embeddings: a Generative Approach for Hypergraphs
Shihao Wu, Junyi Yang, Gongjun Xu +1
Hypergraph data, which capture multi-way interactions among entities, are increasingly prevalent in the big data era. Generating new hyperlinks from an observed, usually high-dimen…