4 citations · 7 across the 18 of their papers we have counts for
19 papers
Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models
Yifu Yuan, Yaoting Huang, Xianze Yao +20
We introduce Embodied-R1.5, a unified Embodied Foundation Model (EFM) that integrates comprehensive embodied reasoning capabilities, spanning embodied cognition, task planning, cor…
UAM: A Dual-Stream Perspective on Forgetting in VLA Training
Jianke Zhang, Yuanfei Luo, Yucheng Hu +6
Vision--language--action (VLA) models are typically built by fine-tuning a pretrained vision--language model (VLM) on action data. However, we show that this standard recipe system…
Veo-Act: Enhancing VLA Policies with Frontier Video Models
Zhongru Zhang, Chenghan Yang, Qingzhou Lu +4
Video generation models can produce coherent vi- sual sequences depicting object motion and interactions. We in- vestigate how frontier video generation models can complement visio…
Realtime-VLA V2: Learning to Run VLAs Fast, Smooth, and Accurate
Chen Yang, Yucheng Hu, Yunchao Ma +3
In deployment of the VLA models to real-world robotic tasks, execution speed matters. In previous work arXiv:2510.26742 we analyze how to make neural computation of VLAs on GPU fas…
BagelVLA: Enhancing Long-Horizon Manipulation via Interleaved Vision-Language-Action Generation
Yucheng Hu, Jianke Zhang, Yuanfei Luo +9
Equipping embodied agents with the ability to reason about tasks, foresee physical outcomes, and generate precise actions is essential for general-purpose manipulation. While recen…
DyTopo: Dynamic Topology Routing for Multi-Agent Reasoning via Semantic Matching
Yuxing Lu, Yucheng Hu, Xukai Zhao +1
Multi-agent systems built from prompted large language models can improve multi-round reasoning, yet most existing pipelines rely on fixed, trajectory-wide communication patterns t…
CLM-Bench: Benchmarking and Analyzing Cross-lingual Misalignment of LLMs in Knowledge Editing
Yucheng Hu, Wei Zhou, Juesi Xiao
Knowledge Editing (KE) has emerged as a promising paradigm for updating facts in Large Language Models (LLMs) without retraining. However, progress in Multilingual Knowledge Editin…
VLM4VLA: Revisiting Vision-Language-Models in Vision-Language-Action Models
Jianke Zhang, Xiaoyu Chen, Qiuyue Wang +7
Vision-Language-Action (VLA) models, which integrate pretrained large Vision-Language Models (VLM) into their policy backbone, are gaining significant attention for their promising…
UniJEPA: Enhancing Robot Policy via Unified Continuous and Discrete Representation Learning
Jianke Zhang, Yucheng Hu, Yanjiang Guo +5
Building generalist robot policies that can handle diverse tasks in open-ended environments is a central challenge in robotics. To leverage knowledge from large-scale pretraining,…
Robix: A Unified Model for Robot Interaction, Reasoning and Planning
Huang Fang, Mengxi Zhang, Heng Dong +6
We introduce Robix, a unified model that integrates robot reasoning, task planning, and natural language interaction within a single vision-language architecture. Acting as the hig…
Language-Guided Tuning: Configuration Optimization for Automated ML Research
Yuxing Lu, Yucheng Hu, Nan Sun +1
Configuration optimization remains a critical bottleneck in machine learning, requiring coordinated tuning across model architecture, training strategy, feature engineering, and hy…
Rethinking Agent Design: From Top-Down Workflows to Bottom-Up Skill Evolution
Jiawei Du, Jinlong Wu, Yuzheng Chen +3
Most LLM-based agent frameworks adopt a top-down philosophy: humans decompose tasks, define workflows, and assign agents to execute each step. While effective on benchmark-style ta…
Improving Vision-Language-Action Model with Online Reinforcement Learning
Yanjiang Guo, Jianke Zhang, Xiaoyu Chen +4
Recent studies have successfully integrated large vision-language models (VLMs) into low-level robotic control by supervised fine-tuning (SFT) with expert robotic datasets, resulti…
UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent
Jianke Zhang, Yanjiang Guo, Yucheng Hu +3
Recent advancements in Vision-Language-Action (VLA) models have leveraged pre-trained Vision-Language Models (VLMs) to improve the generalization capabilities. VLMs, typically pre-…
Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations
Yucheng Hu, Yanjiang Guo, Pengchao Wang +6
Visual representations play a crucial role in developing generalist robotic policies. Previous vision encoders, typically pre-trained with single-image reconstruction or two-image…
Prediction with Action: Visual Policy Learning via Joint Denoising Process
Yanjiang Guo, Yucheng Hu, Jianke Zhang +4
Diffusion models have demonstrated remarkable capabilities in image generation tasks, including image editing and video creation, representing a good understanding of the physical…
HiRT: Enhancing Robotic Control with Hierarchical Robot Transformers
Jianke Zhang, Yanjiang Guo, Xiaoyu Chen +4
Large Vision-Language-Action (VLA) models, leveraging powerful pre trained Vision-Language Models (VLMs) backends, have shown promise in robotic control due to their impressive gen…
RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing
Yucheng Hu, Yuxing Lu
Large Language Models (LLMs) have catalyzed significant advancements in Natural Language Processing (NLP), yet they encounter challenges such as hallucination and the need for doma…
Relevant or Random: Can LLMs Truly Perform Analogical Reasoning?
Chengwei Qin, Wenhan Xia, Tan Wang +5
Analogical reasoning is a unique ability of humans to address unfamiliar challenges by transferring strategies from relevant past experiences. One key finding in psychology is that…