Datasets:

JunsWan
/

AgentViSS

license: mit
pretty_name: AgentViSS
language:
  - en
size_categories:
  - n<1K
tags:
  - multimodal
  - social-simulation
  - visual-social-intelligence
  - multi-agent-simulation
configs:
  - config_name: default
    data_files:
      - split: train
        path: train.jsonl

AgentViSS Dataset

This repository contains the public data package for AgentViSS: Can Agents Read the Room? Benchmarking Visual Social Intelligence in Multimodal Simulation.

Files

.
+-- README.md
+-- train.jsonl
+-- data.json
+-- images/
    +-- scenario_001/
    |   +-- group_labeled.png
    |   +-- individual/
    |       +-- character_01.jpg
    |       +-- character_02.jpg
    +-- ...

train.jsonl is a viewer-friendly table with 240 AgentViSS records. It exposes key fields from data.json and keeps image path columns at the end.
data.json contains the canonical full records.
images/ contains all image assets referenced by data.json.
Image paths in data.json are package-relative. Resolve them from the dataset repository root.
All images are resized proportionally so that the longest edge is at most 512 pixels.

Dataset Structure

Each record includes an anonymized scenario id, dialogue type, conflict level, characters, role-level information, goals, emotions, and image paths.

The Hugging Face Dataset Viewer is configured to read train.jsonl rather than the raw images/ directory. This keeps the viewer organized around the 240 scenario records instead of displaying the 282 image files as separate rows.

Important image fields:

group_image_labeled: path to the scenario-level group image.
individual_images: mapping from character names to role portrait paths.

Example:

{
  "id": "agentviss_low_01",
  "source_scenario": "scenario_001",
  "group_image_labeled": "images/scenario_001/group_labeled.png",
  "individual_images": {
    "CharacterName": "images/scenario_001/individual/character_01.jpg"
  }
}

The fields base_json_path, group_image, background, and individual_informations.*.personality are not included in this public data package.

Download

Download the full dataset, including images, with huggingface_hub:

import json
from pathlib import Path
from huggingface_hub import snapshot_download

root = Path(snapshot_download(
    repo_id="JunsWan/AgentViSS",
    repo_type="dataset",
))

records = json.loads((root / "data.json").read_text(encoding="utf-8"))
first_group_image = root / records[0]["group_image_labeled"]

For the flattened viewer table:

import json
from pathlib import Path
from huggingface_hub import snapshot_download

root = Path(snapshot_download(
    repo_id="JunsWan/AgentViSS",
    repo_type="dataset",
))

with (root / "train.jsonl").open(encoding="utf-8") as f:
    rows = [json.loads(line) for line in f]

You can also clone the repository:

git clone https://huggingface.co/datasets/JunsWan/AgentViSS