Omkar2118/datasets huggingface dataset:
Enoch Oluwumi
Full name: Enoch Okikijesu Oluwumi

Briefly describe the dataset. Provide:

* a high-level explanation of the dataset characteristics
* explain motivations and summary of its content
* potential use cases of the dataset

If the description or image is from a different paper, please refer to it as follows:
Source: [title](url)
Image Source: [title](url)
Visuomotor affordance learning (VAL) robot interaction dataset

This data contains about 2500 trajectories (with images and actions) of a Sawyer robot interacting with various objects.

Examples from the dataset are shown in the adjacent video. We provide two versions of the VAL dataset - one with low-res images (1.4 GB) and one with high-res images (162 GB). The data quantity and format is the same between these two versions; the difference is only the image observation quality.

The smaller dataset, with 48x48x3 images which can be used for eg. offline RL, is available for direct download: <https://drive.google.com/file/d/1UuWANkVtWLg4egIK2LB_YCKuF87rMQ1H/view?usp=sharing>

The larger dataset, with 480x640x3 which might be preferred for eg. representation learning, is available at this Google drive folder:  <https://drive.google.com/drive/folders/1kD9kyP7-RlIrSnuN7rpEASAGWp5qnNov?usp=sharing>

To download the larger dataset, we suggest using https://rclone.org/

The data is sorted into several folders. There are a total of 300 files and 2500 trajectories.
- fixed_drawer - Human-controlled demonstration data opening and closing drawers. (~10%)
- fixed_pnp - Human-controlled demonstration data picking up objects. (~10%)
- fixed_pot - Human-controlled demonstration data interacting with a pot and a lid. (~10%)
- fixed_tray - Human-controlled demonstration data picking up objects and placing it in a tray. (~10%)
- general - Further human-controlled demonstration data collected with the most diversity and variation. (~40%)
- onpolicy_eval - Evaluation data collected by an RL policy. (~10%)
- onpolicy_expl - Exploration data collected by an RL policy. (~10%)

Introducing paper: What Can I Do Here? Learning New Skills by Imagining Visual Affordances
PS5k
Full name: presentation-slide-pairs

We introduce a new data set containing 5000 scientific papers and their slides crawled from conference proceeding websites such as aclweb and usenix.
SemEval-2013 Task-2

The **SemEval-2013 Task 2** dataset contains data for two subtasks: A, an expression-level subtask, and B, a message-level subtask. Crowdsourcing was used to label a large Twitter training dataset along with additional test sets of Twitter and SMS messages for both subtasks.

Introducing paper: SemEval-2013 Task 2: Sentiment Analysis in Twitter