6 citations · 13 across the 9 of their papers we have counts for
9 papers
Users as Annotators: LLM Preference Learning from Comparison Mode
Zhongze Cai, Xiaocheng Li
Pairwise preference data have played an important role in the alignment of large language models (LLMs). Each sample of such data consists of a prompt, two different responses to t…
What Matters in Data for DPO?
Yu Pan, Zhongze Cai, Guanting Chen +2
Direct Preference Optimization (DPO) has emerged as a simple and effective approach for aligning large language models (LLMs) with human preferences, bypassing the need for a learn…
Incentivizing High-Quality Human Annotations with Golden Questions
Shang Liu, Zhongze Cai, Hanzhao Wang +2
Human-annotated data plays a vital role in training large language models (LLMs), such as supervised fine-tuning and human preference alignment. However, it is not guaranteed that…
Out-of-distribution Robust Optimization
Zhongze Cai, Hansheng Jiang, Xiaocheng Li
In this paper, we consider the contextual robust optimization problem under an out-of-distribution setting. The contextual robust optimization problem considers a risk-sensitive ob…
Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification
Shang Liu, Zhongze Cai, Guanting Chen +1
Predicting simple function classes has been widely used as a testbed for developing theory and understanding of the trained Transformer's in-context learning (ICL) ability. In this…
Towards Better Statistical Understanding of Watermarking LLMs
Zhongze Cai, Shang Liu, Hanzhao Wang +2
In this paper, we study the problem of watermarking large language models (LLMs). We consider the trade-off between model distortion and detection ability and formulate it as a con…
A Neural Network Based Choice Model for Assortment Optimization
Hanzhao Wang, Zhongze Cai, Xiaocheng Li +1
Discrete-choice models are used in economics, marketing and revenue management to predict customer purchase probabilities, say as a function of prices and other features of the off…
Distribution-Free Model-Agnostic Regression Calibration via Nonparametric Methods
Shang Liu, Zhongze Cai, Xiaocheng Li
In this paper, we consider the uncertainty quantification problem for regression models. Specifically, we consider an individual calibration objective for characterizing the quanti…
Deep Learning for Choice Modeling
Zhongze Cai, Hanzhao Wang, Kalyan Talluri +1
Choice modeling has been a central topic in the study of individual preference or utility across many fields including economics, marketing, operations research, and psychology. Wh…