mind2web
Datasets
All datasets matching “mind2web”Multimodal-Mind2Web
Dataset Summary
Multimodal-Mind2Web is the multimodal version of Mind2Web, a dataset for developing and evaluating generalist agents
for the web that can follow language instructions to complete complex tasks on any website. In this dataset, we align each HTML document in the dataset with
its corresponding webpage screenshot image from the Mind2Web raw dump. This multimodal version addresses the inconvenience of loading images from the ~300GB Mind2Web Raw Dump.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/osunlp/Multimodal-Mind2Web.mind2web-utg-crawl-outputsMind2Web
Dataset Card for Dataset Name
Dataset Summary
Mind2Web is a dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website. Existing datasets for web agents either use simulated websites or only cover a limited set of websites and tasks, thus not suitable for generalist web agents. With over 2,000 open-ended tasks collected from 137 websites spanning 31 domains and crowdsourced action… See the full description on the dataset page: https://huggingface.co/datasets/osunlp/Mind2Web.mind2web_multimodal_test_domain
Dataset Card for "Cross-Domain" Test Split in Multimodal Mind2Web
Note: This dataset is the test split of the Cross-Domain dataset introduced in the paper.
This is a FiftyOne dataset with 4050 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/mind2web_multimodal_test_domain.mind2web_multimodal_test_task
Dataset Card for Multimodal Mind2Web "Cross-Task" Test Split
Note: This dataset is the test split of the Cross-Task dataset introduced in the paper.
This is a FiftyOne dataset with 1338 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/mind2web_multimodal_test_task.MNL_Mind2Web_APPWorld
Mistake Notebook Learning (MNL) Dataset
Our work has been acepted by ACL 2026
Project Code | Paper
⭐ If you find this project helpful, please give us a star on GitHub! It means a lot to us.
Github:https://github.com/Bairong-Xdynamics/MistakeNotebookLearning
Mistake Notebook Learning (MNL) is a novel, training-free memory framework that enables Large Language Model (LLM) agents to systematically learn from their mistakes. This repository contains the training and evaluation… See the full description on the dataset page: https://huggingface.co/datasets/MultiSense/MNL_Mind2Web_APPWorld.