activity
20242026
most citedVision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models

3 citations · 4 across the 9 of their papers we have counts for

collaborators

14 papers

cs.RO2026

From Failures to Learnable Worlds: Policy-Conditioned Environment Generation for Navigation Agents

Yue Zhang, Han Lin, Zun Wang +3

Simulated environments enable scalable training data generation for embodied agents, but more data does not necessarily provide what a particular agent needs to learn. Existing env…

cs.CV2026

Data-Centric Recursive Self-Improvement for Navigation via Policy-Synchronized Language-Action Dual Bootstrapping

Songze Li, Haoming Gu, Ziyang Gong +11

Vision-language navigation requires agents to follow natural-language instructions to reach target locations, making high-quality language supervision essential. Since human annota…

cs.CV2026

Seeing Isn't Knowing: Do VLMs Know When Not to Answer Spatial Questions (and Why)?

Yue Zhang, Zun Wang, Han Lin +3

Spatial reasoning benchmarks typically evaluate whether vision-language models can derive the correct answer from a visual observation. Yet in real 3D environments, the observation…

cs.CV2026

PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation

Yidong Huang, Zun Wang, Han Lin +6

Generating realistic human motion is a central yet unsolved challenge in video generation. While reinforcement learning (RL)-based post-training has driven recent gains in general…

cs.CV2026

V-Co: A Closer Look at Visual Representation Alignment via Co-Denoising

Han Lin, Xichen Pan, Zun Wang +4

Pixel-space diffusion has recently re-emerged as a strong alternative to latent diffusion, enabling high-quality generation without pretrained autoencoders. However, standard pixel…

cs.CV2026

AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories

Zun Wang, Han Lin, Jaehong Yoon +3

Maintaining spatial world consistency over long horizons remains a central challenge for camera-controllable video generation. Existing memory-based approaches often condition gene…

cs.CV2026

When and How Much to Imagine: Adaptive Test-Time Scaling with World Models for Visual Spatial Reasoning

Shoubin Yu, Yue Zhang, Zun Wang +4

Despite rapid progress in MLLMs, visual spatial reasoning remains unreliable when correct answers depend on how a scene would appear under unseen or alternative viewpoints. Recent…

cs.CV2025

Planning with Sketch-Guided Verification for Physics-Aware Video Generation

Yidong Huang, Zun Wang, Han Lin +5

Recent video generation approaches increasingly rely on planning intermediate control signals such as object trajectories to improve temporal coherence and motion fidelity. However…

cs.CV2025

Learning Goal-Oriented Vision-and-Language Navigation with Self-Improving Demonstrations at Scale

Songze Li, Zun Wang, Gengze Zhou +8

Goal-oriented vision-language navigation requires robust exploration capabilities for agents to navigate to specified goals in unknown environments without step-by-step instruction…

cs.CV2025

EPiC: Efficient Video Camera Control Learning with Precise Anchor-Video Guidance

Zun Wang, Jaemin Cho, Jialu Li +4

Recent approaches for video generation with camera control often create anchor videos (i.e., rendered videos that approximate desired camera motions) to guide diffusion models as a…

cs.CV2024

SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of Experts

Gengze Zhou, Yicong Hong, Zun Wang +3

The academic field of learning instruction-guided visual navigation can be generally categorized into high-level category-specific search and low-level language-guided navigation,…

cs.CV2024★ 1 cited

DreamRunner: Fine-Grained Compositional Story-to-Video Generation with Retrieval-Augmented Motion Adaptation

Zun Wang, Jialu Li, Han Lin +2

Storytelling video generation (SVG) aims to produce coherent and visually rich multi-scene videos that follow a structured narrative. Existing methods primarily employ LLM for high…

cs.CV2024

NavGPT-2: Unleashing Navigational Reasoning Capability for Large Vision-Language Models

Gengze Zhou, Yicong Hong, Zun Wang +2

Capitalizing on the remarkable advancements in Large Language Models (LLMs), there is a burgeoning initiative to harness LLMs for instruction following robotic navigation. Such a t…

cs.CL2024★ 3 cited

Vision-and-Language Navigation Today and Tomorrow: A Survey in the Era of Foundation Models

Yue Zhang, Ziqiao Ma, Jialu Li +6

Vision-and-Language Navigation (VLN) has gained increasing attention over recent years and many approaches have emerged to advance their development. The remarkable achievements of…