alphaFeedback
LC
cs.ROcs.CVcs.AIcs.LGcs.GR

On Valency

published · living versions
W_d5eabf98·v1 · currentpublished
Rollback: Experience Backtracking in World Models for Policy Improvement
with Jiayi Luo, Yang Zhang, Nan Wang, Chen Gao +11
1 version

Preprints & journals

12 papers in the corpus · 2022–2026
WorldOracle: Benchmarking Action-Conditioned World Models against Real-World Executions2610.18826v4 · Haoyi Duan, Liliang Chen, Nan Wang et al.2026 · 0 citationsarXiv
GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation2609.05588v3 · Renhang Liu, Wenzhi Zhao, Zhuo Yang et al.2026 · 0 citationsarXiv
Act2Goal: From World Model To General Goal-conditioned Policy2512.23541v1 · Pengfei Zhou, Liliang Chen, Shengcong Chen et al.2025 · 0 citationsarXiv
Real2Edit2Real: Generating Robotic Demonstrations via a 3D Control Interface2512.19402v2 · Yujie Zhao, Hongwei Fan, Di Chen et al.2025 · 0 citationsarXiv
Fidelity-Aware Data Composition for Robust Robot Generalization2509.24797v1 · Zizhao Tong, Di Chen, Sicheng Hu et al.2025 · 0 citationsarXiv
Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation2508.05635v3 · Yue Liao, Pengfei Zhou, Siyuan Huang et al.2025 · 0 citationsarXiv
EWMBench: Evaluating Scene, Motion, and Semantic Quality in Embodied World Models2505.09694v2 · Hu Yue, Siyuan Huang, Yue Liao et al.2025 · 0 citationsarXiv
EnerVerse-AC: Envisioning Embodied Environments with Action Condition2505.09723v1 · Yuxin Jiang, Shengcong Chen, Siyuan Huang et al.2025 · 1 citationarXiv
EnerVerse: Envisioning Embodied Future Space for Robotics Manipulation2501.01895v3 · Siyuan Huang, Liliang Chen, Pengfei Zhou et al.2025 · 0 citationsarXiv
UnconFuse: Avatar Reconstruction from Unconstrained Images2211.10098v1 · Han Huang, Liliang Chen, Xihao Wang2022 · 1 citationarXiv
Career total: 13 works. 12 are in this corpus.

Profile built from the corpus for this byline.

Author records are still filling in while the Hub is in alpha. If this is your page, you'll be able to claim it soon. Spot a mistake? Tell us.