6 citations · 15 across the 11 of their papers we have counts for
12 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…
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…
How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators
Shang Liu, Hanzhao Wang, Zhongyao Ma +1
Human-annotated preference data play an important role in aligning large language models (LLMs). In this paper, we study two connected questions: how to monitor the quality of huma…
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 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…
Transformer Choice Net: A Transformer Neural Network for Choice Prediction
Hanzhao Wang, Xiaocheng Li, Kalyan Talluri
Discrete-choice models, such as Multinomial Logit, Probit, or Mixed-Logit, are widely used in Marketing, Economics, and Operations Research: given a set of alternatives, the custom…
Learning to Make Adherence-Aware Advice
Guanting Chen, Xiaocheng Li, Chunlin Sun +1
As artificial intelligence (AI) systems play an increasingly prominent role in human decision-making, challenges surface in the realm of human-AI interactions. One challenge arises…
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…
When No-Rejection Learning is Consistent for Regression with Rejection
Xiaocheng Li, Shang Liu, Chunlin Sun +1
Learning with rejection has been a prototypical model for studying the human-AI interaction on prediction tasks. Upon the arrival of a sample instance, the model first uses a rejec…
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…
Learning to Sell a Focal-ancillary Combination
Hanzhao Wang, Xiaocheng Li, Kalyan Talluri
A number of products are sold in the following sequence: First a focal product is shown, and if the customer purchases, one or more ancillary products are displayed for purchase. A…