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20192026
most citedA Survey on Vision-Language-Action Models for Embodied AI

29 citations · 70 across the 33 of their papers we have counts for

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Showing 2025Show all

12 papers · 1 filter

cs.CV2025

EVLP:Learning Unified Embodied Vision-Language Planner with Reinforced Supervised Fine-Tuning

Xinyan Cai, Shiguang Wu, Dafeng Chi +4

In complex embodied long-horizon manipulation tasks, effective task decomposition and execution require synergistic integration of textual logical reasoning and visual-spatial imag…

cs.RO2025

EchoVLA: Robotic Vision-Language-Action Model with Synergistic Declarative Memory for Mobile Manipulation

Min Lin, Xiwen Liang, Bingqian Lin +12

Recent progress in Vision-Language-Action (VLA) models has enabled embodied agents to interpret multimodal instructions and perform complex tasks. However, existing VLAs are mostly…

cs.RO2025

More than A Point: Capturing Uncertainty with Adaptive Affordance Heatmaps for Spatial Grounding in Robotic Tasks

Xinyu Shao, Yanzhe Tang, Pengwei Xie +6

Many language-guided robotic systems rely on collapsing spatial reasoning into discrete points, making them brittle to perceptual noise and semantic ambiguity. To address this chal…

cs.RO2025

Embodied Arena: A Comprehensive, Unified, and Evolving Evaluation Platform for Embodied AI

Fei Ni, Min Zhang, Pengyi Li +34

Embodied AI development significantly lags behind large foundation models due to three critical challenges: (1) lack of systematic understanding of core capabilities needed for Emb…

cs.RO2025

OmniEVA: Embodied Versatile Planner via Task-Adaptive 3D-Grounded and Embodiment-aware Reasoning

Yuecheng Liu, Dafeng Chi, Shiguang Wu +10

Recent advances in multimodal large language models (MLLMs) have opened new opportunities for embodied intelligence, enabling multimodal understanding, reasoning, and interaction,…

cs.CV2025

ActionSink: Toward Precise Robot Manipulation with Dynamic Integration of Action Flow

Shanshan Guo, Xiwen Liang, Junfan Lin +3

Language-instructed robot manipulation has garnered significant interest due to the potential of learning from collected data. While the challenges in high-level perception and pla…

cs.RO2025

AutoLayout: Closed-Loop Layout Synthesis via Slow-Fast Collaborative Reasoning

Weixing Chen, Dafeng Chi, Yang Liu +7

The automated generation of layouts is vital for embodied intelligence and autonomous systems, supporting applications from virtual environment construction to home robot deploymen…

cs.AI2025

MineAnyBuild: Benchmarking Spatial Planning for Open-world AI Agents

Ziming Wei, Bingqian Lin, Zijian Jiao +5

Spatial Planning is a crucial part in the field of spatial intelligence, which requires the understanding and planning about object arrangements in space perspective. AI agents wit…

cs.CV2025

Structured Preference Optimization for Vision-Language Long-Horizon Task Planning

Xiwen Liang, Min Lin, Weiqi Ruan +6

Existing methods for vision-language task planning excel in short-horizon tasks but often fall short in complex, long-horizon planning within dynamic environments. These challenges…

cs.RO2025

Mem2Ego: Empowering Vision-Language Models with Global-to-Ego Memory for Long-Horizon Embodied Navigation

Lingfeng Zhang, Yuecheng Liu, Zhanguang Zhang +19

Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have made them powerful tools in embodied navigation, enabling agents to leverage commonsense…

cs.CL2025★ 1 cited

3D-MoE: Towards Spatial Intelligence with Mixture-of-Experts for 3D Reasoning and Action Generation

Yueen Ma, Zenglin Xu, Yuzheng Zhuang +2

Spatial intelligence, encompassing 3D perception and reasoning, is the essential next frontier of AI. Scaling current 3D vision-language models (VLMs) that rely on dense Transforme…

cs.RO2025★ 1 cited

SpatialCoT: Advancing Spatial Reasoning through Coordinate Alignment and Chain-of-Thought for Embodied Task Planning

Yuecheng Liu, Dafeng Chi, Shiguang Wu +13

Spatial reasoning is an essential problem in embodied AI research. Efforts to enhance spatial reasoning abilities through supplementary spatial data and fine-tuning have proven lim…