imageszlab-princeton/Vero-600kvisual-reasoningreinforcement-learningmultimodalvision-languagevlmrl-trainingimage-textapache-2.0
Vero-600K: Multi-Task Visual Reasoning RL Dataset
About this data
600K curated reinforcement learning samples from 59 datasets across 6 visual reasoning categories for training and evaluating vision-language models.
Schema
| Name | Type | Description |
|---|---|---|
| id | VARCHAR | Unique identifier combining source dataset name, sample index, and hash |
| data_source | VARCHAR | Name of the originating dataset among 59 sources (e.g., geo170k, chartqa) |
| prompt | STRUCT("role" VARCHAR[], "content" VARCHAR[]) | Conversation structure with role (user/assistant) and content strings for VLM input |
| ability | VARCHAR | Visual reasoning category: stem, chart_ocr, spatial_action, or other of 6 types |
| reward_model | STRUCT(style VARCHAR, ground_truth VARCHAR) | Reward signal specification with style (rule/learned) and ground_truth answer |
| extra_info | STRUCT(split VARCHAR, "index" BIGINT, "domain" VARCHAR, answer VARCHAR, question VARCHAR, reward_type VARCHAR, tolerance DOUBLE) | Metadata including train/val/test split, source domain, question text, answer, reward type, and tolerance threshold |
| image | STRUCT(bytes BLOB, path VARCHAR) | Visual input as binary blob and/or file path reference |
Sample Data
Preview a sample of the data before downloading.
Free
Open dataset
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Seller: DataBazaar
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Via MCP Server
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "Vero-600K: Multi-Task Visual R" })
// Found: 16ddd4b5-805d-482c-85fa-bac79745d51f
get_download_url({ dataset_id: "16ddd4b5-805d-482c-85fa-bac79745d51f" }) // free — no API key neededVia REST API
# Free dataset — no API key required: curl https://api.databazaar.io/datasets/16ddd4b5-805d-482c-85fa-bac79745d51f/download-url