Author

Yang Liu

Observed name: Liu, Yang

Institutions: Tongji University, University of Minnesota, Sun Yat-sen University, Peking University, Fudan University, University of Minnesota System, Huazhong University of Science and Technology, Beihang University, Tsinghua University

Observed institutions: Tongji University, University of Minnesota, Sun Yat-sen University, Peking University, Fudan University, University of Minnesota System, Huazhong University of Science and Technology, Beihang University, Tsinghua University

OpenAlex ID: A5158770188

PILOT: Guiding Long-Horizon World-Model Planning for Robot Manipulation with Visual Subgoals and Policy Priors

2026 · Liu, Yang, Cui, Hanchen, et al. · arXiv (Cornell University) · 1

Adaptive-Group Process Rewards for GUI Agents

2026 · Shang, Zirui, Liu, Yang, et al. · arXiv (Cornell University)

Preliminary Exploration of Large Models Based on Self-Supervised Learning for Health Monitoring of Power Electronic Converters

2026 · Liao, Xinyuan, Deng, Xiangtian, et al. · arXiv (Cornell University)

Instructions Are Evidence, Not Objectives: Measuring Outcome Alignment of Agents

2026 · Liu, Kaiming, Liu, Yuxuan, et al. · arXiv (Cornell University)

Benchmarking Self-Supervised 3D Medical Vision Foundation Models and Transferability Estimation

2026 · Tang, Jiaqi, Wang, Yu, et al. · arXiv (Cornell University)

PRB-WM: Physics-Regularized Beta World Models for Predictive Link Adaptation on Real Time-Varying Underwater Acoustic Channels

2026 · Zhong, Shengjie, Zhao, Zhongliang, et al. · arXiv (Cornell University)

Approaching Irrational Quantization

2026 · Wu, Zhihong, Chen, Zhimou, et al. · arXiv (Cornell University)

We Have Been Interpreting Diffusion Transformer Backbone Behaviors Wrong

2026 · Meng, Benyuan, Huang, Longtao, et al. · arXiv (Cornell University)

Predict in Chunks, Revise in Spans: History-conditioned Action Regeneration for Robotic Manipulation

2026 · Wang, Chenyang, Wang, Yuntian, et al. · arXiv (Cornell University)

PEARL: Process-Experience Aware Reinforcement Learning for Multi-Turn Agents

2026 · Yang, Jie, Huang, Mianqiu, et al. · arXiv (Cornell University)

Works count: 10

Citation count: 1

H-index: 1

I10-index: