17 citations · 29 across the 29 of their papers we have counts for
29 papers
SCOUT: Unlocking Enhanced Spatial Reasoning via Structured Chain-of-Thought and Multi-Objective Process Reward
Zile Zhou, Huining Yuan, Weichen Zhang +2
Existing Vision-Language Models (VLMs) exhibits a critical bottleneck in robust spatial reasoning. Recent reinforcement learning (RL) methods aim to close this gap with verifiable…
ActiveFly-Bench: Aligning Embodied Question Answering with Vision-Language-Action for Aerial Embodied Perception
Weichen Zhang, Shiquan Yu, Yinan Zhu +9
We introduce ActiveFly-Bench, the first benchmark to bridge cyberspace reasoning and physical-world interaction for UAV embodied perception. The benchmark decomposes active percept…
Uncertainty-Aware World Model for Aerial Image-Goal Navigation
Deyi Zhu, Haoyu Fan, Yinan Zhu +4
Aerial image-goal navigation requires an unmanned aerial vehicle (UAV) to reach a target location specified by a goal image. Existing world-model-based methods rank candidate traje…
Learning an Interior Layout Policy in a Domain Specific Language Action Space
Yuhao Lu, Weichen Zhang, Wenyi Xiao +2
Indoor scene layout generation is a challenging task in interior design. Existing methods often oversimplify the task by reducing room conditions to coarse 3D bounding boxes and ne…
Worldscape-MoE: A Unified Mixture-of-Experts World Model for Scalable Heterogeneous Action Control
Jianjie Fang, Yongyan Xu, Ziyou Wang +13
World models are rapidly becoming a core infrastructure for embodied intelligence and interactive agents: they provide controllable simulators in which agents can perceive, act, fo…
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +355
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
WorldFly: A World-Model-Based Vision-Language-Action Model for UAV Navigation
Shengtao Zheng, Kai Li, Weichen Zhang +5
End-to-end Vision-Language-Action (VLA) models have shown promise in UAV navigation. However, existing approaches typically rely on historical observations to directly predict acti…
A Case for Agentic Tuning: From Documentation to Action in PostgreSQL
Hongyu Lin, Mingyu Li, Weichen Zhang +4
Documentation has long guided computer system tuning by distilling expert knowledge into per-parameter recommendations. Yet such guides capture only what experts conclude, discardi…
WorldVLN: Autoregressive World Action Model for Aerial Vision-Language Navigation
Baining Zhao, Jiacheng Xu, Weicheng Feng +13
Aerial vision-language navigation (VLN) requires agents to follow natural-language instructions through closed-loop perception and action in 3D environments. We argue that aerial V…
iWorld-Bench: A Benchmark for Interactive World Models with a Unified Action Generation Framework
Jianjie Fang, Yingshan Lei, Qin Wan +8
Achieving Artificial General Intelligence (AGI) requires agents that learn and interact adaptively, with interactive world models providing scalable environments for perception, re…
How Far Are Large Multimodal Models from Human-Level Spatial Action? A Benchmark for Goal-Oriented Embodied Navigation in Urban Airspace
Baining Zhao, Ziyou Wang, Jianjie Fang +8
Large multimodal models (LMMs) show strong visual-linguistic reasoning but their capacity for spatial decision-making and action remains unclear. In this work, we investigate wheth…
Neural Latent Arbitrary Lagrangian-Eulerian Grids for Fluid-Solid Interaction
Shilong Tao, Zhe Feng, Shaohan Chen +3
Fluid-solid interaction (FSI) problems are fundamental in many scientific and engineering applications, yet effectively capturing the highly nonlinear two-way interactions remains…
Aerial World Model for Long-horizon Visual Generation and Navigation in 3D Space
Weichen Zhang, Peizhi Tang, Xin Zeng +12
Unmanned aerial vehicles (UAVs) have emerged as powerful embodied agents. One of the core abilities is autonomous navigation in large-scale three-dimensional environments. Existing…
SynSeg: Feature Synergy for Multi-Category Contrastive Learning in End-to-End Open-Vocabulary Semantic Segmentation
Weichen Zhang, Kebin Liu, Fan Dang +3
Semantic segmentation in open-vocabulary scenarios presents significant challenges due to the wide range and granularity of semantic categories. Existing weakly-supervised methods…
AdaptInfer: Adaptive Token Pruning for Vision-Language Model Inference via Dynamical Text Guidance
Weichen Zhang, Zhui Zhu, Ningbo Li +5
Vision-language models (VLMs) have achieved impressive performance on multimodal inference tasks, but the cost remains a significant challenge due to the large number of vision tok…
iPanda: An LLM-based Agent for Automated Conformance Testing of Communication Protocols
Xikai Sun, Fan Dang, Shiqi Jiang +8
Conformance testing is essential for ensuring that protocol implementations comply with their specifications. However, traditional testing approaches involve manually creating nume…
MIRAGE-Bench: LLM Agent is Hallucinating and Where to Find Them
Weichen Zhang, Yiyou Sun, Pohao Huang +3
Hallucinations pose critical risks for large language model (LLM)-based agents, often manifesting as hallucinative actions resulting from fabricated or misinterpreted information w…
Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report
Shanghai AI Lab, :, Xiaoyang Chen +35
To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, this report presents a comprehensive assessment of their frontier…
AirScape: An Aerial Generative World Model with Motion Controllability
Baining Zhao, Rongze Tang, Mingyuan Jia +9
How to enable agents to predict the outcomes of their own motion intentions in three-dimensional space has been a fundamental problem in embodied intelligence. To explore general s…
IS-Bench: Evaluating Interactive Safety of VLM-Driven Embodied Agents in Daily Household Tasks
Xiaoya Lu, Zeren Chen, Xuhao Hu +5
Flawed planning from VLM-driven embodied agents poses significant safety hazards, hindering their deployment in real-world household tasks. However, existing static, non-interactiv…
CityNavAgent: Aerial Vision-and-Language Navigation with Hierarchical Semantic Planning and Global Memory
Weichen Zhang, Chen Gao, Shiquan Yu +6
Aerial vision-and-language navigation (VLN), requiring drones to interpret natural language instructions and navigate complex urban environments, emerges as a critical embodied AI…
The Point, the Vision and the Text: Does Point Cloud Boost Spatial Reasoning of Large Language Models? A Bias-Controlled Study
Weichen Zhang, Ruiying Peng, Xin Zeng +9
3D Large Language Models (LLMs) leveraging spatial information in point clouds for 3D spatial reasoning attract great attention. Despite some promising results, the advantages of p…
UrbanVideo-Bench: Benchmarking Vision-Language Models on Embodied Intelligence with Video Data in Urban Spaces
Baining Zhao, Jianjie Fang, Zichao Dai +8
Large multimodal models exhibit remarkable intelligence, yet their embodied cognitive abilities during motion in open-ended urban 3D space remain to be explored. We introduce a ben…
Open3D-VQA: A Benchmark for Comprehensive Spatial Reasoning with Multimodal Large Language Model in Open Space
Weichen Zhang, Zile Zhou, Xin Zeng +7
Spatial reasoning is a fundamental capability of multimodal large language models (MLLMs), yet their performance in open aerial environments remains underexplored. In this work, we…