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20222026
most citedZeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference

1 citations · 1 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2026

SP3O: Reinforcement Learning from Segment Preferences without Reward Modeling

Evan Assmus, Qining Zhang, Lei Ying

Preference-based reinforcement learning (PbRL) for general stochastic MDPs often requires training a reward model. Existing reward-model-free methods are either restricted to bandi…

cs.LG2026

Efficient Federated RLHF via Zeroth-Order Policy Optimization

Deyi Wang, Qining Zhang, Lei Ying

This paper considers reinforcement learning from human feedback in a federated learning setting with resource-constrained agents, such as edge devices. We propose an efficient fede…

cs.CV2025

Early Lung Cancer Diagnosis from Virtual Follow-up LDCT Generation via Correlational Autoencoder and Latent Flow Matching

Yutong Wu, Yifan Wang, Qining Zhang +2

Lung cancer is one of the most commonly diagnosed cancers, and early diagnosis is critical because the survival rate declines sharply once the disease progresses to advanced stages…

cs.LG2025

Sign-SZPO: Provable Preference-based Reinforcement Learning with an Unknown Link Function

Qining Zhang, Lei Ying

The link function, which characterizes the relationship between the preference for two trajectories and their returns, is a crucial component in designing RL algorithms that learn…

cs.LG2025

Multi-Metric Adaptive Experimental Design Under a Fixed Budget with Validation

Qining Zhang, Tanner Fiez, Yi Liu +1

A/B tests in online experiments face statistical power challenges when testing multiple candidates simultaneously, while adaptive experimental designs (AED) alone fall short in inf…

cs.LG2024★ 1 cited

Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference

Qining Zhang, Lei Ying

Reward inference (learning a reward model from human preferences) is a critical intermediate step in the Reinforcement Learning from Human Feedback (RLHF) pipeline for fine-tuning…

cs.LG2024

Reinforcement Learning from Human Feedback without Reward Inference: Model-Free Algorithm and Instance-Dependent Analysis

Qining Zhang, Honghao Wei, Lei Ying

In this paper, we study reinforcement learning from human feedback (RLHF) under an episodic Markov decision process with a general trajectory-wise reward model. We developed a mode…

cs.LG2024

Cost Aware Best Arm Identification

Kellen Kanarios, Qining Zhang, Lei Ying

In this paper, we study a best arm identification problem with dual objects. In addition to the classic reward, each arm is associated with a cost distribution and the goal is to i…

cs.LG2023

Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms

Qining Zhang, Lei Ying

This paper considers a stochastic Multi-Armed Bandit (MAB) problem with dual objectives: (i) quick identification and commitment to the optimal arm, and (ii) reward maximization th…

stat.AP2022

On Low-Complexity Quickest Intervention of Mutated Diffusion Processes Through Local Approximation

Qining Zhang, Honghao Wei, Weina Wang +1

We consider the problem of controlling a mutated diffusion process with an unknown mutation time. The problem is formulated as the quickest intervention problem with the mutation m…