datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
v41-quant-workerWebRSSBenchWe will update our bench on 2025.10.20
worker-safety-qa-eval
Dataset Card for Worker Safety Question and Answer Eval
This dataset contains the worker-safety-qa-eval benchmark. This benchmark is used to evaluate question answering tasks in the domain of worker safety and health.
The focus of the benchmark is to answer queries about worker safety practices and regulations based on laws in Singapore.
For correct answers we refer to the resources from Workplace Safety and Health Council.
Dataset Details
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/codelion/worker-safety-qa-eval.knowledge-worker-search-bench
Knowledge-Worker Search Bench
40 multi-channel retrieval tasks over realistic synthetic knowledge-worker
environments, generated with Tonic Fabricate.
Each task drops an agent into one persona's work world — mail (Outlook or
Gmail), Slack, Google Docs, calendar, attachments — and asks a question a real
chief-of-staff-style assistant would get: "brief me for tomorrow's sync",
"where did we land on the renewal, and what forced the timeline?". Answering
requires finding and… See the full description on the dataset page: https://huggingface.co/datasets/TonicAI/knowledge-worker-search-bench.workers-comp-coverage-thresholds-by-state
Workers' compensation insurance requirements by US state: employee thresholds, who counts, and industry exceptions
Canonical, always-current version: https://referencesource.org/workers-comp-coverage-thresholds-by-state/
Machine-readable: https://referencesource.org/workers-comp-coverage-thresholds-by-state/data.json — this mirror is a point-in-time copy.
Last verified: 2026-08-12
Stale after: 2027-02-08 (past this date, prefer the canonical copy —
it re-verifies on a cadence… See the full description on the dataset page: https://huggingface.co/datasets/referencesource/workers-comp-coverage-thresholds-by-state.state-worker-classification-tests
State Worker Classification Tests — Independent Contractor vs Employee
Canonical, always-current version: https://referencesource.org/state-worker-classification-tests/
Machine-readable: https://referencesource.org/state-worker-classification-tests/data.json — this mirror is a point-in-time copy.
Last verified: 2026-08-18
Stale after: 2027-08-18 (past this date, prefer the canonical copy —
it re-verifies on a cadence this snapshot does not)
Records: 10
Which legal test each… See the full description on the dataset page: https://huggingface.co/datasets/referencesource/state-worker-classification-tests.Welding-Workers-Without-Protective-Gear-Violation-Detection-Dataset
Welding Workers Without Protective Gear Violation Detection Dataset
In the current industrial field, welding operations pose significant safety risks, especially when workers do not wear necessary protective equipment, which can easily lead to eye injuries. However, existing safety monitoring systems mostly rely on manual inspection, which is inefficient and cannot provide real-time feedback. To effectively improve worker safety, this dataset aims to automatically recognize whether… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Welding-Workers-Without-Protective-Gear-Violation-Detection-Dataset.langfuse-worker-imagegig-worker-fraud-narratives_with_reasoning
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
gig_worker_fraud_narratives
This dataset contains prompts designed to generate first-person narratives from gig economy workers who have experienced various types of financial fraud, such as account takeovers, hacking, and social engineering. Each prompt specifies details including the fraud vector, financial instrument involved, transaction amount, and sender age to guide the creation of… See the full description on the dataset page: https://huggingface.co/datasets/Nachammai41/gig-worker-fraud-narratives_with_reasoning.kanitakorn-thaiexam-v29-literature-rhetoric-worker-g-20260614kanitakorn-thaiexam-v29-grammar-loanword-worker-i-20260614gig-worker-fraud-narratives
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
gig_worker_fraud_narratives
This dataset contains prompts designed to generate first-person narratives from gig economy workers who have experienced various types of financial fraud, such as account takeover, hacking, and social engineering. Each prompt specifies details like the fraud vector, financial instrument, transaction amount, and sender age to guide the creation of realistic scam… See the full description on the dataset page: https://huggingface.co/datasets/Nachammai41/gig-worker-fraud-narratives.kanitakorn-thaiexam-v29-thai-language-precision-worker-e-20260614kanitakorn-thaiexam-v29-social-civics-worker-h-20260614workers-rights-advisory-indic
Workers' Rights Advisory (Hindi/Punjabi)
Native Hindi and Punjabi text from
ai4bharat/IndicCorpV2,
adapted with AutoScientist into substantive domain responses written by
a workers'-rights advisor identifying the issue and concrete next steps.
Rows
561
Unique source texts
561
Absolute quality score
8.8/10 (grade B)
Source score before adaptation
9.0/10 (grade A)
Percentile
43.9
Relative change
-2.2%
Median response length
569 chars… See the full description on the dataset page: https://huggingface.co/datasets/tojpaj/workers-rights-advisory-indic.digital-workers-ai-agent
Digital Workers Agent Meta and Traffic Dataset in AI Agent Marketplace | AI Agent Directory | AI Agent Index from DeepNLP
This dataset is collected from AI Agent Marketplace Index and Directory at http://www.deepnlp.org, which contains AI Agents's meta information such as agent's name, website, description, as well as the monthly updated Web performance metrics, including Google,Bing average search ranking positions, Github Stars, Arxiv References, etc.
The dataset is helpful for AI… See the full description on the dataset page: https://huggingface.co/datasets/DeepNLP/digital-workers-ai-agent.