49 citations · 174 across the 38 of their papers we have counts for
10 papers · 1 filter
WorldExam: Benchmarking World Models from Apparent Appearance to Inherent Reactivity
Yuxue Yang, Shuyao Shang, Jiahe Wang +13
Controllable video generation models are increasingly being developed as world models. Accordingly, evaluating them in this role extends beyond the apparent appearance of generated…
PhiZero: A World Model Built Around Physical Language
Shuyao Shang, Yuqi Wang, Ruopeng Gao +4
We introduce PhiZero, a physical world model built around physical language, a compact discrete representation of world-state transitions. Existing physical world models typically…
World Pilot: Steering Vision-Language-Action Models with World-Action Priors
Zefu Lin, Rongxu Cui, Junjia Xu +4
Vision-Language-Action (VLA) models inherit semantic grounding from large-scale pretraining and perform competently across in-distribution manipulation tasks. This grounding, howev…
DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo
Hanwen Wang, Weizhi Zhao, Xiangyu Wang +11
Achieving human-level manipulation requires dexterous robotic hands capable of complex object interactions. Advancing such capabilities further demands standardized benchmarks for…
ReinDriveGen: Reinforcement Post-Training for Out-of-Distribution Driving Scene Generation
Hao Zhang, Lue Fan, Weikang Bian +4
We present ReinDriveGen, a framework that enables full controllability over dynamic driving scenes, allowing users to freely edit actor trajectories to simulate safety-critical cor…
DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving
Shuyao Shang, Bing Zhan, Yunfei Yan +9
We propose DynVLA, a driving VLA model that introduces a new CoT paradigm termed Dynamics CoT. DynVLA forecasts compact world dynamics before action generation, enabling more infor…
GA-Drive: Geometry-Appearance Decoupled Modeling for Free-viewpoint Driving Scene Generation
Hao Zhang, Lue Fan, Qitai Wang +5
A free-viewpoint, editable, and high-fidelity driving simulator is crucial for training and evaluating end-to-end autonomous driving systems. In this paper, we present GA-Drive, a…
CLI-Gym: Scalable CLI Task Generation via Agentic Environment Inversion
Yusong Lin, Haiyang Wang, Shuzhe Wu +4
Agentic coding requires agents to effectively interact with runtime environments, e.g., command line interfaces (CLI), so as to complete tasks like resolving dependency issues, fix…
FeatureBench: Benchmarking Agentic Coding for Complex Feature Development
Qixing Zhou, Jiacheng Zhang, Haiyang Wang +9
Agents powered by large language models (LLMs) are increasingly adopted in the software industry, contributing code as collaborators or even autonomous developers. As their presenc…
NeoVerse: Enhancing 4D World Model with in-the-wild Monocular Videos
Yuxue Yang, Lue Fan, Ziqi Shi +3
In this paper, we propose NeoVerse, a versatile 4D world model that is capable of 4D reconstruction, novel-trajectory video generation, and rich downstream applications. We first i…