具身智能領域取得新突破，機器人企業越疆發佈自研世界動作模型“空弈DobotWAM”具身大模型，標誌着其在複雜現實任務理解與執行上邁出關鍵一步。該模型在業內標準評測基準LIBERO上通過深度測試，順利通過LIBERO-Spatial、LIBERO-Object等評估，驗證了核心能力。
高德開源全球首個統一架構機器人具身操作基座模型ABot-M0，旨在通過“一個通用大腦適配多種形態機器人”打破異構硬件壁壘，加速具身智能在工業與家庭場景的應用。該模型在Libero-Plus等權威基準測試中展現出卓越性能，標誌着具身智能領域的重要進展。
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上下文長度
Tacoin
這是Tacoin基於NVIDIA GR00T模型在LIBERO libero long基準測試上進行微調的機器人操作模型。該模型採用雙RGB流和8自由度狀態輸入，能夠預測16步關節空間動作，專門用於長視野機器人操作任務。
VLA-Adapter
VLA-Adapter是一種在Libero-Spatial上訓練的微型視覺語言動作模型，採用Prismatic-VLM架構，僅使用Qwen2.5-0.5B作為大語言模型主幹。該模型在機器人基準測試中超越了參數規模更大的開源VLA模型，實現了高性能的視覺-語言-動作理解與執行。
Hume-vla
Hume-Libero_Object是一個在Libero-Object數據集上訓練的雙系統視覺-語言-動作模型，具備系統2思維能力，適用於機器人領域的研究和應用。
Hume-Libero_Goal是一個基於雙系統思維的視覺-語言-動作模型，專為機器人任務設計，融合了System-2思維以提高決策能力。
moojink
OpenVLA-OFT是基於OpenVLA模型優化的視覺-語言-動作模型，通過微調技術在LIBERO任務套件上顯著提升了執行速度和成功率。
mbreuss
FlowerVLA是一個針對機器人操作任務預訓練的視覺-語言-動作流策略模型，訓練數據來自LIBERO 10數據集，僅包含10億參數。
openvla
該模型是通過在LIBERO-10數據集上採用LoRA方法微調OpenVLA 7B模型得到的視覺語言動作模型，適用於機器人技術領域。
這是一個在LIBERO-Goal數據集上使用LoRA技術微調的OpenVLA 7B視覺語言動作模型，適用於機器人技術領域。
這是一個在LIBERO-Object數據集上使用LoRA微調的OpenVLA 7B視覺-語言-動作模型，專為機器人技術設計。
在LIBERO-Spatial數據集上使用LoRA微調的OpenVLA 7B視覺語言動作模型
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