keplerccc/Robo2VLM-1
Robo2VLM: Visual Question Answering from Large-Scale In-the-Wild Robot Manipulation Datasets Abstract Vision-Language Models (VLMs) acquire real-world knowledge and general reasoning ability through Internet-scale image-text corpora. They can augment robotic systems with scene understanding and task planning, and assist visuomotor policies that are trained on robot trajectory data. We explore the reverse paradigm - using rich, real, multi-modal robot trajectory… See the full description on the dataset page: https://huggingface.co/datasets/keplerccc/Robo2VLM-1.
| Author / organization | keplerccc |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 5.3K (as reported by Hugging Face) |
| Likes | 20 |
| Created | 9 May 2025 |
| Last updated at source | 22 October 2025 |
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- 17 Oct 2026 Description: Robo2VLM: Visual Question Answering from Large-Scale In-the-Wild Robot Manipulation Datasets Abstract Vision-Language Models (VLMs) acquire real-world knowledge and general reasoning ability through Internet-scale image-text corpora. They c → Robo2VLM: Visual Question Answering from Large-Scale In-the-Wild Robot Manipulation Datasets Abstract Vision-Language Models (VLMs) acquire real-world knowledge and general reasoning ability through Internet-scale image-text corpora. They c
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