datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Real-UI-Clickboxes
RUC: Real UI Clickboxes
Click carefully, even when the page is trying to trick you! 👀
Official Hugging Face release for RUC: Real UI Clickboxes, the dataset accompanying our ACL 2026 paper Don't Click That: Teaching Web Agents to Resist Deceptive Interfaces on deceptive UI understanding for web agents.
ACL Anthology: https://aclanthology.org/2026.acl-long.310/
PDF: https://aclanthology.org/2026.acl-long.310.pdf
DOI: https://doi.org/10.18653/v1/2026.acl-long.310… See the full description on the dataset page: https://huggingface.co/datasets/DUDE-Framework/Real-UI-Clickboxes.fitllm-fit-census
Local LLM Fit Census v1 — 2026-09-13
10,530 verdicts: 30 models × 93 devices (36 GPUs + 57 Mac configs) × per-platform quant tiers.
Each row is generated by fitllm-engine from architecture inputs pinned to official config.json files. Runtime and OS reserves remain documented estimates. Reproduce it yourself: npm run census.
Assumptions: context = min(8K, model max) · KV cache F16 · platform reserve/headroom per engine. Interactive per-combo pages: fitllm.run/can-i-run.… See the full description on the dataset page: https://huggingface.co/datasets/click6067/fitllm-fit-census.cli-commands-explained
Overview
This dataset is a collection of 16,098 command line instructions sourced from Commandlinefu and Cheatsheets. It includes an array of commands, each with an id, title, description, date, url to source, author, votes, and flag indicating if the description is AI generated. The descriptions are primarily authored by the original contributors, for entries where descriptions were absent, they have been generated using NeuralBeagle14-7B. Out of the total entries, 10,039… See the full description on the dataset page: https://huggingface.co/datasets/b-mc2/cli-commands-explained.clickhouse-server-imageProduct_reviews_click_stream_Dataasingle-click_bench
Single-Click Benchmark for Web Interaction
This benchmark defines a minimal web interaction task that requires only a single click to complete.
Each instance includes two task formulations (simplified and human-like), a pre-saved HTML file for obtaining screenshots or metadata, and target annotations with the element’s bounding box and XPath for evaluation.
The dataset enables systematic evaluation of web agents’ capabilities such as visual grounding, task understanding, and action… See the full description on the dataset page: https://huggingface.co/datasets/alexandrayakovleva/single-click_bench.5k-dataset-geogpt-fineweb5k-dataset-geogpt-fineweb-random