25 citations · 44 across the 23 of their papers we have counts for
24 papers
Policy Optimization and Statistical Inference for Online Contextual Matrix Games
Liner Xiang, Yixin Wang, Hengrui Cai
Online decision making often requires navigating a landscape shaped by both dynamic contexts and strategic interactions. In competitive pricing, for example, hotels must account fo…
PABU: Progress-Aware Belief Update for Efficient LLM Agents
Haitao Jiang, Lin Ge, Hengrui Cai +1
Large Language Model (LLM) agents commonly condition actions on full action-observation histories, which introduce task-irrelevant information that easily leads to redundant action…
Text Rationalization for Robust Causal Effect Estimation
Lijinghua Zhang, Hengrui Cai
Recent advances in natural language processing have enabled the increasing use of text data in causal inference, particularly for adjusting confounding factors in treatment effect…
Foresighted Online Policy Optimization with Interference
Liner Xiang, Jiayi Wang, Hengrui Cai
Contextual bandits, which leverage the baseline features of sequentially arriving individuals to optimize cumulative rewards while balancing exploration and exploitation, are criti…
Correct Reasoning Paths Visit Shared Decision Pivots
Dongkyu Cho, Amy B. Z. Zhang, Bilel Fehri +4
Chain-of-thought (CoT) reasoning exposes the intermediate thinking process of large language models (LLMs), yet verifying those traces at scale remains unsolved. In response, we in…
Time-Varying Home Field Advantage in Football: Learning from a Non-Stationary Causal Process
Minhao Qi, Hengrui Cai, Guanyu Hu +1
In sports analytics, home field advantage is a robust phenomenon where the home team wins more games than the away team. However, discovering the causal factors behind home field a…
A Review of Causal Decision Making
Lin Ge, Hengrui Cai, Runzhe Wan +2
To make effective decisions, it is important to have a thorough understanding of the causal relationships among actions, environments, and outcomes. This review aims to surface thr…
Conformal Diffusion Models for Individual Treatment Effect Estimation and Inference
Hengrui Cai, Huaqing Jin, Lexin Li
Estimating treatment effects from observational data is of central interest across numerous application domains. Individual treatment effect offers the most granular measure of tre…
On Efficient Inference of Causal Effects with Multiple Mediators
Haoyu Wei, Hengrui Cai, Chengchun Shi +1
This paper provides robust estimators and efficient inference of causal effects involving multiple interacting mediators. Most existing works either impose a linear model assumptio…
Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuning
Hengrui Cai, Shengjie Liu, Rui Song
This paper introduces a causal attribution model to enhance the interpretability of large language models (LLMs) and improve their causal reasoning abilities via precise fine-tunin…
Towards Trustworthy Explanation: On Causal Rationalization
Wenbo Zhang, Tong Wu, Yunlong Wang +2
With recent advances in natural language processing, rationalization becomes an essential self-explaining diagram to disentangle the black box by selecting a subset of input texts…
Sequential Knockoffs for Variable Selection in Reinforcement Learning
Tao Ma, Jin Zhu, Hengrui Cai +4
In real-world applications of reinforcement learning, it is often challenging to obtain a state representation that is parsimonious and satisfies the Markov property without prior…
Heterogeneous Synthetic Learner for Panel Data
Ye Shen, Runzhe Wan, Hengrui Cai +1
In the new era of personalization, learning the heterogeneous treatment effect (HTE) becomes an inevitable trend with numerous applications. Yet, most existing HTE estimation metho…
On Learning Necessary and Sufficient Causal Graphs
Hengrui Cai, Yixin Wang, Michael Jordan +1
The causal revolution has stimulated interest in understanding complex relationships in various fields. Most of the existing methods aim to discover causal relationships among all…
On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs
Richard A Watson, Hengrui Cai, Xinming An +2
Heterogeneity and comorbidity are two interwoven challenges associated with various healthcare problems that greatly hampered research on developing effective treatment and underst…
How Much Does Home Field Advantage Matter in Soccer Games? A Causal Inference Approach for English Premier League Analysis
Chen Wang, Katherine Price, Hengrui Cai +3
In many sports, it is commonly believed that the home team has an advantage over the visiting team, known as the home field advantage. Yet its causal effect on team performance is…
Jump Interval-Learning for Individualized Decision Making
Hengrui Cai, Chengchun Shi, Rui Song +1
An individualized decision rule (IDR) is a decision function that assigns each individual a given treatment based on his/her observed characteristics. Most of the existing works in…
Doubly Robust Interval Estimation for Optimal Policy Evaluation in Online Learning
Ye Shen, Hengrui Cai, Rui Song
Evaluating the performance of an ongoing policy plays a vital role in many areas such as medicine and economics, to provide crucial instructions on the early-stop of the online exp…
CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search
Hengrui Cai, Wenbin Lu, Rachel Marceau West +2
Personalized medicine, a paradigm of medicine tailored to a patient's characteristics, is an increasingly attractive field in health care. An important goal of personalized medicin…
Periodic-GP: Learning Periodic World with Gaussian Process Bandits
Hengrui Cai, Zhihao Cen, Ling Leng +1
We consider the sequential decision optimization on the periodic environment, that occurs in a wide variety of real-world applications when the data involves seasonality, such as t…
GEAR: On Optimal Decision Making with Auxiliary Data
Hengrui Cai, Rui Song, Wenbin Lu
Personalized optimal decision making, finding the optimal decision rule (ODR) based on individual characteristics, has attracted increasing attention recently in many fields, such…
Calibrated Optimal Decision Making with Multiple Data Sources and Limited Outcome
Hengrui Cai, Wenbin Lu, Rui Song
We consider the optimal decision-making problem in a primary sample of interest with multiple auxiliary sources available. The outcome of interest is limited in the sense that it i…
Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings
Hengrui Cai, Chengchun Shi, Rui Song +1
We consider off-policy evaluation (OPE) in continuous treatment settings, such as personalized dose-finding. In OPE, one aims to estimate the mean outcome under a new treatment dec…
A Threshold-free Prospective Prediction Accuracy Measure for Censored Time to Event Data
Yan Yuan, Qian M. Zhou, Bingying Li +3
Prediction performance of a risk scoring system needs to be carefully assessed before its adoption in clinical practice. Clinical preventive care often uses risk scores to screen a…