ecot-openvla-7b-oxe: A policy that was initially trained on the Open-X-Embodiment dataset actions, fine-tuned on the mixture of OXE action-only data and our reasonings for Bridge for another 20k steps. embodied_features_bridge: A dataset of the embodied features and reasonings collected for Bridge demonstrations.

2024年7月25日 · Embodied-CoT/ecot-openvla-7b-oxe. Robotics • Updated Jul 10, 2024 • 1.05k datasets 1

from prismatic.util.cot_utils import CotTag, abbreviate_tag from prismatic.util.data_utils import tree_map from prismatic.vla.action_tokenizer import ActionTokenizer

Embodied-CoT / ecot-openvla-7b-oxe. like 0. Robotics. Transformers. Safetensors. openvla. feature-extraction. custom_code. arxiv: 1910.09700. Model card Files Files and versions Community Train Use this model Edit model card Model Card for Model ID.

Embodied Chain of Thought: A robotic policy that reason to solve the task. - MichalZawalski/embodied-CoT

前言：思维链，是一个非常新的AI概念。强大的逻辑推理是大语言模型“智能涌现”出的核心能力之一，好像AI有了人的意识一样。而推理能力的关键在于——思维链（Chain of Thought，CoT）。对于复杂问题（尤其是复杂…

CoT是一个三元组<输入，思维链，输出>输入，在Prompt的样例中，给出CoT的形式输入，LLM在回答时会模仿CoT的形式给出中间推理的步骤，并且给出最终结果。在某种程度上，LLM的推理逻辑此时对LLM使用者是一个白盒，可以清楚的看出LLM的推理逻辑是否有误，最终 ...

大模型通过思维链cot将复杂问题分解为多个中间步骤，展示出了强大的推理能力，大模型的思维链cot主要分为两大范式： 零样本链式思维（ Zero-Shot-CoT ） ：与任务无关，在测试问题之后添加一个如“让我们一步一步思考”的单一提示语，以促进LLMs中的推理链条。

OpenVLA: An Open-Source Vision-Language-Action Model. Paper • 2406.09246 • Published Jun 13, 2024 • 36 oier-mees

2024年12月16日 · Generating Chain-of-Thought (CoT) before deriving the answer can effectively improve the reasoning capabilities of large language models (LLMs) and significantly improve the accuracy of the generated answer. However, in most cases, the length of the generated CoT is much longer than the desired final answer, which results in additional decoding costs. Furthermore, existing research has ...