具身智能领域取得新突破，机器人企业越疆发布自研世界动作模型“空弈DobotWAM”具身大模型，标志着其在复杂现实任务理解与执行上迈出关键一步。该模型在业内标准评测基准LIBERO上通过深度测试，顺利通过LIBERO-Spatial、LIBERO-Object等评估，验证了核心能力。
高德开源全球首个统一架构机器人具身操作基座模型ABot-M0，旨在通过“一个通用大脑适配多种形态机器人”打破异构硬件壁垒，加速具身智能在工业与家庭场景的应用。该模型在Libero-Plus等权威基准测试中展现出卓越性能，标志着具身智能领域的重要进展。
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Tacoin
这是Tacoin基于NVIDIA GR00T模型在LIBERO libero long基准测试上进行微调的机器人操作模型。该模型采用双RGB流和8自由度状态输入，能够预测16步关节空间动作，专门用于长视野机器人操作任务。
VLA-Adapter
VLA-Adapter是一种在Libero-Spatial上训练的微型视觉语言动作模型，采用Prismatic-VLM架构，仅使用Qwen2.5-0.5B作为大语言模型主干。该模型在机器人基准测试中超越了参数规模更大的开源VLA模型，实现了高性能的视觉-语言-动作理解与执行。
Hume-vla
Hume-Libero_Object是一个在Libero-Object数据集上训练的双系统视觉-语言-动作模型，具备系统2思维能力，适用于机器人领域的研究和应用。
Hume-Libero_Goal是一个基于双系统思维的视觉-语言-动作模型，专为机器人任务设计，融合了System-2思维以提高决策能力。
moojink
OpenVLA-OFT是基于OpenVLA模型优化的视觉-语言-动作模型，通过微调技术在LIBERO任务套件上显著提升了执行速度和成功率。
mbreuss
FlowerVLA是一个针对机器人操作任务预训练的视觉-语言-动作流策略模型，训练数据来自LIBERO 10数据集，仅包含10亿参数。
openvla
该模型是通过在LIBERO-10数据集上采用LoRA方法微调OpenVLA 7B模型得到的视觉语言动作模型，适用于机器人技术领域。
这是一个在LIBERO-Goal数据集上使用LoRA技术微调的OpenVLA 7B视觉语言动作模型，适用于机器人技术领域。
这是一个在LIBERO-Object数据集上使用LoRA微调的OpenVLA 7B视觉-语言-动作模型，专为机器人技术设计。
在LIBERO-Spatial数据集上使用LoRA微调的OpenVLA 7B视觉语言动作模型
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