68 citations · 159 across the 38 of their papers we have counts for
43 papers
EviSeek: An Evidence-Centric Agentic Framework for Embodied Active Information Seeking
Jintao Li, Zhiyong Cao, Baihua Xiao +2
Active embodied question answering requires agents to acquire evidence through viewpoint changes and physical interaction. The central challenge is to avoid undirected interaction:…
When the Past Shapes Action: Understanding Embodied Memory
Siqi Li, Ziyi Bai, Xinrun Xu +2
Recent advances in generative foundation models have expanded the capabilities of embodied AI, enabling increasingly general navigation, manipulation, and long-horizon task executi…
ViLoMan: Learning Visual-Proprioceptive Whole-Body Loco-Manipulation Skills for Humanoid Robots
Zejie Tian, Ruibing Hou, Bingpeng Ma +2
Humanoid loco-manipulation requires adaptive whole-body coordination to seamlessly integrate locomotion and physical interaction. Despite recent advances, learning autonomous loco-…
WAVE-Go: World-Model Navigation with Adaptive Execution for Wheel-Legged Robots
Mingyi Li, Ji Li, Zhihao Ouyang +2
World models can anticipate the consequences of navigation actions, but predicted action sequences may become invalid during execution, especially when wheel-legged robots encounte…
PRACTICE: From Experience to Expertise in Self-Evolving Embodied Agents
Ziyi Bai, Siqi Li, Tinglei Huang +1
Recent studies have shown that multimodal large language models (MLLMs) can serve as embodied agents, translating language instructions and visual observations into executable plan…
LectūraAgents: A Multi-Agent Framework for Adaptive Personalized AI-Assisted Learning and Embodied Teaching
Jaward Sesay, Yue Yu, Siwei Dong +1
Effective personalized AI-assisted learning demands systems that can not only generate accurate learner-specific educational materials, but also dynamically adapt their instruction…
X-DiffVLA: X-Embodied Diffusion Action Heads for Vision-Language-Action Models
Boyu Li, Chaoyi Xu, Haoqi Yuan +5
Learning universal policies from cross-embodied data remains a fundamental challenge in robotics. Although Vision-Language-Action (VLA) models are pre-trained on large and diverse…
HandwritingAgent: Language-Driven Handwriting Synthesis in Scalable Vector Space
Jaward Sesay, Yue Yu, Börje F. Karlsson
Teaching machines to emulate natural handwriting styles remains an open challenge, as it requires synthesizing stroke sequences that dynamically vary in shape, texture, pressure an…
ExoActor: Exocentric Video Generation as Generalizable Interactive Humanoid Control
Yanghao Zhou, Jingyu Ma, Yibo Peng +3
Humanoid control systems have made significant progress in recent years, yet modeling fluent interaction-rich behavior between a robot, its surrounding environment, and task-releva…
ICPRL: Acquiring Physical Intuition from Interactive Control
Xinrun Xu, Pi Bu, Ye Wang +8
VLMs excel at static perception but falter in interactive reasoning in dynamic physical environments, which demands planning and adaptation to dynamic outcomes. Existing physical r…
EgoActor: Grounding Task Planning into Spatial-aware Egocentric Actions for Humanoid Robots via Visual-Language Models
Yu Bai, MingMing Yu, Chaojie Li +3
Deploying humanoid robots in real-world settings is fundamentally challenging, as it demands tight integration of perception, locomotion, and manipulation under partial-information…
RANGER: A Monocular Zero-Shot Semantic Navigation Framework through Visual Contextual Adaptation
Ming-Ming Yu, Yi Chen, Börje F. Karlsson +1
Efficient target localization and autonomous navigation in complex environments are fundamental to real-world embodied applications. While recent advances in multimodal foundation…
SWITCH: Benchmarking Modeling and Handling of Tangible Interfaces in Long-horizon Embodied Scenarios
Juntao Cheng, Wanyue Zhang, Zhiwei Yu +7
Tangible control interfaces (TCIs), such as appliance panels, remotes, elevators, and embedded GUIs, are a fundamental component of everyday human-built environments. Interacting w…
Towards Proprioception-Aware Embodied Planning for Dual-Arm Humanoid Robots
Boyu Li, Siyuan He, Hang Xu +10
In recent years, Multimodal Large Language Models (MLLMs) have demonstrated the ability to serve as high-level planners, enabling robots to follow complex human instructions. Howev…
DeepPHY: Benchmarking Agentic VLMs on Physical Reasoning
Xinrun Xu, Pi Bu, Ye Wang +7
Although Vision Language Models (VLMs) exhibit strong perceptual abilities and impressive visual reasoning, they struggle with attention to detail and precise action planning in co…
DualTHOR: A Dual-Arm Humanoid Simulation Platform for Contingency-Aware Planning
Boyu Li, Siyuan He, Hang Xu +9
Developing embodied agents capable of performing complex interactive tasks in real-world scenarios remains a fundamental challenge in embodied AI. Although recent advances in simul…
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Samuel Cahyawijaya, Holy Lovenia, Joel Ruben Antony Moniz +89
Southeast Asia (SEA) is a region of extraordinary linguistic and cultural diversity, yet it remains significantly underrepresented in vision-language (VL) research. This often resu…
Taking Notes Brings Focus? Towards Multi-Turn Multimodal Dialogue Learning
Jiazheng Liu, Sipeng Zheng, Börje F. Karlsson +1
Multimodal large language models (MLLMs), built on large-scale pre-trained vision towers and language models, have shown great capabilities in multimodal understanding. However, mo…
Being-0: A Humanoid Robotic Agent with Vision-Language Models and Modular Skills
Haoqi Yuan, Yu Bai, Yuhui Fu +6
Building autonomous robotic agents capable of achieving human-level performance in real-world embodied tasks is an ultimate goal in humanoid robot research. Recent advances have ma…
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
Angelika Romanou, Negar Foroutan, Anna Sotnikova +56
The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…
MLLM as Retriever: Interactively Learning Multimodal Retrieval for Embodied Agents
Junpeng Yue, Xinrun Xu, Börje F. Karlsson +1
MLLM agents demonstrate potential for complex embodied tasks by retrieving multimodal task-relevant trajectory data. However, current retrieval methods primarily focus on surface-l…
SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages
Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar +58
Southeast Asia (SEA) is a region rich in linguistic diversity and cultural variety, with over 1,300 indigenous languages and a population of 671 million people. However, prevailing…
A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges
Xinrun Xu, Yuxin Wang, Chaoyi Xu +4
The swift evolution of Large-scale Models (LMs), either language-focused or multi-modal, has garnered extensive attention in both academy and industry. But despite the surge in int…
Cradle: Empowering Foundation Agents Towards General Computer Control
Weihao Tan, Wentao Zhang, Xinrun Xu +25
Despite the success in specific scenarios, existing foundation agents still struggle to generalize across various virtual scenarios, mainly due to the dramatically different encaps…