Yibin Wang

Yibin Wang

(he/him)

First-year Ph.D. student

Rutgers University

Professional Summary

I am a first-year Ph.D. student in the Computer Science Department at Rutgers University, where I am advised by Prof. Chengzhi Mao. I am currently studying post-training for MoE LLMs and world models. My goal is to improve model post-training through efficient, streamlined methods. I also use Bayesian approaches to enhance the trustworthiness and reliability of LLMs.

From such a gentle thing, from such a fountain of all delight, my every pain is born.
—— Michelangelo

Education

Ph.D. Computer Science

2026-09-01
Present

Rutgers University

B.E. Computer Science

2019-09-01
2024-05-31

Huazhong University of Science and Technology

Interests

LLM thinking Bayesian LLMs Trustworthy AI
Featured Publications
Recent Publications
Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
NeurIPS 2025
TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning
ICLR 2026
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models
NeurIPS 2025
Continual learning of large language models: A comprehensive survey
ACM Computing Surveys
Teaching

Fall 2026 — Teaching Assistant, Rutgers University

CS 461: Machine Learning Principles

Instructor: Bernhard Firner

Blogs
Misc