Datasets:
Upload Hegarty dataset with 2x3 design structure
Browse files- README.md +132 -0
- lab_mental_reasoning.parquet +3 -0
- lab_perspective_taking.parquet +3 -0
- lab_visual_access.parquet +3 -0
- real_mental_reasoning.parquet +3 -0
- real_visual_access.parquet +3 -0
README.md
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---
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license: cc-by-4.0
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task_categories:
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- visual-question-answering
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- multiple-choice
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language:
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- en
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pretty_name: Hegarty Dataset
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size_categories:
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- 10K<n<100K
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tags:
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- spatial-reasoning
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- perspective-taking
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- visual-reasoning
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- cognitive-science
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- vision-language
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configs:
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- config_name: lab_visual_access
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description: Lab setting - Visual Access Reasoning (Can you see X from viewpoint Y?)
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- config_name: lab_mental_reasoning
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description: Lab setting - Mental Reasoning (Spatial relationships between objects)
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- config_name: lab_perspective_taking
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description: Lab setting - Perspective-Taking Reasoning (What can another observer see?)
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- config_name: real_visual_access
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description: Real-world setting - Visual Access Reasoning
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- config_name: real_mental_reasoning
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description: Real-world setting - Mental Reasoning
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- config_name: real_perspective_taking
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description: Real-world setting - Perspective-Taking Reasoning
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---
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# Hegarty Dataset
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## ποΈ Overview
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The **Hegarty Dataset** is a comprehensive benchmark for evaluating spatial reasoning and perspective-taking abilities in vision-language models. Inspired by Piaget's classic Three Mountains Task, this dataset provides a systematic evaluation across three cognitive dimensions in both controlled lab and real-world settings.
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## π Dataset Structure
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### 2Γ3 Design
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- **2 Settings**: Lab (controlled) and Real-world
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- **3 Task Types**:
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- **Visual Access Reasoning**: Determining object visibility from different viewpoints
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- **Mental Reasoning**: Understanding spatial relationships between objects
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- **Perspective-Taking Reasoning**: Understanding what others can see from their viewpoint
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### Dataset Statistics
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| Setting | Task Type | Samples | Description |
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|---------|-----------|---------|-------------|
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| Lab | Visual Access | ~1,000 | Controlled geometric scenarios |
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| Lab | Mental Reasoning | ~500 | Spatial relationship tasks |
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| Lab | Perspective-Taking | ~300 | Other-perspective understanding |
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| Real | Visual Access | ~2,000 | Real-world ego-exo scenarios |
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| Real | Mental Reasoning | ~2,000 | Natural spatial reasoning |
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| Real | Perspective-Taking | ~2,000 | Real-world perspective-taking |
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## π― Task Descriptions
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### Visual Access Reasoning (formerly Perspective-Taking L1)
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- **Question**: "Can you see object X from viewpoint Y?"
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- **Format**: Binary (Yes/No) or Multiple Choice
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- **Cognitive Ability**: Basic visual perspective-taking
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### Mental Reasoning (formerly Spatiality)
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- **Question**: "What is the spatial relationship between objects?"
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- **Format**: Multiple Choice (4 options)
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- **Cognitive Ability**: Spatial reasoning and mental rotation
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### Perspective-Taking Reasoning (formerly Perspective-Taking L2)
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- **Question**: "What can the observer at position X see?"
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- **Format**: Multiple Choice (4 options)
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- **Cognitive Ability**: Theory of mind and advanced perspective-taking
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## π‘ Usage
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```python
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from datasets import load_dataset
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# Load specific configuration
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dataset = load_dataset("Hokin/hegarty", "lab_visual_access")
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# Load all lab settings
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lab_data = {
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'visual_access': load_dataset("Hokin/hegarty", "lab_visual_access"),
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'mental_reasoning': load_dataset("Hokin/hegarty", "lab_mental_reasoning"),
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'perspective_taking': load_dataset("Hokin/hegarty", "lab_perspective_taking")
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}
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# Load all real-world settings
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real_data = {
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'visual_access': load_dataset("Hokin/hegarty", "real_visual_access"),
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'mental_reasoning': load_dataset("Hokin/hegarty", "real_mental_reasoning"),
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'perspective_taking': load_dataset("Hokin/hegarty", "real_perspective_taking")
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}
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```
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## π Model Performance
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Current state-of-the-art models show significant gaps compared to human performance:
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- **Humans**: 80-93% accuracy across all tasks
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- **Best AI Models**: 30-55% accuracy
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- **Key Finding**: Models perform better on visual access than mental reasoning or perspective-taking
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## π Related Resources
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- **Paper**: [Coming Soon]
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- **GitHub**: [grow-ai-like-a-child/hegarty](https://github.com/grow-ai-like-a-child/hegarty)
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- **Leaderboard**: [Coming Soon]
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## π Citation
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```bibtex
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@dataset{three_mountain_2024,
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title={Hegarty: A Comprehensive Benchmark for Spatial Reasoning and Perspective-Taking},
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author={Hokin Deng and Contributors},
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year={2024},
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publisher={HuggingFace}
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}
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```
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## π License
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This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
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## π€ Contributing
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We welcome contributions! Please see our GitHub repository for guidelines.
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## π·οΈ Tags
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`spatial-reasoning` `perspective-taking` `visual-reasoning` `cognitive-science` `vision-language` `benchmark` `evaluation`
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lab_mental_reasoning.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:0bf593464e407c9933df9f57d74a8f8f5152dd82dffcd674afad606b84ac3e17
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size 100887513
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lab_perspective_taking.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:c5b63a07c806a57f0aedb7b2925e104e3695dd97c9466d1acf0d6e5de15dc60e
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size 6769823
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lab_visual_access.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:f8f122e7902f2341dede176e003c249dc36565ba6bef07ad8faeb3af5e3dd10f
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size 38719856
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real_mental_reasoning.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:96b478e0547800fdd84b32fe8644d2991d612fc81aa139597a6ae7a957174c78
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size 335283266
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real_visual_access.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:6c15f0c52e4f061bd8d717a605e54fdfa50b0a7d0b31eb47f8a04e2d67b58d32
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size 235691390
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