6 citations · 15 across the 11 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…