Update README.md

README.md

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 pretty_name: HandVQA
 size_categories:
 - 1M<n<10M
----
+---
+
+
+# HandVQA: Diagnosing and Improving Fine-Grained Spatial Reasoning about Hands in Vision-Language Models
+
+HandVQA is a large-scale diagnostic benchmark designed to evaluate fine-grained spatial reasoning in vision-language models (VLMs), focusing on articulated hand pose understanding.
+
+It contains over **1.6 million multiple-choice questions (MCQs)** derived from 3D hand annotations, probing joint-level relationships such as angles, distances, and relative positions.
+
+## Dataset Description
+
+### Motivation
+Despite strong performance on general VQA tasks, VLMs struggle with fine-grained spatial reasoning, especially for articulated structures like human hands.
+
+HandVQA is designed to diagnose these limitations by evaluating:
+- Joint angle understanding
+- Inter-joint distances
+- Relative spatial positions (X, Y, Z)
+
+### Data Sources
+The dataset is built from:
+- FreiHAND
+- InterHand2.6M
+- FPHA
+
+using their 3D hand joint annotations.
+
+## Task Format
+
+Each sample consists of:
+- An image of a hand
+- A multiple-choice question (MCQ)
+- 4 candidate answers
+- 1 correct answer
+
+### Subtasks
+HandVQA includes 5 categories:
+1. Angle
+2. Distance
+3. Relative Position (X-axis)
+4. Relative Position (Y-axis)
+5. Relative Position (Z-axis)
+
+Each question probes a specific geometric relation between hand joints.
+
+## Example
+
+**Question:**
+From the options below, choose the correct description.
+
+**Options:**
+A. The middle finger is bent completely inward at the distal interphalangeal joint.
+B. The middle finger is bent inward at the distal interphalangeal joint.  
+C. The middle finger is bent slightly inward at the distal interphalangeal joint.
+D. The middle finger is straight at the distal interphalangeal joint.
+
+**Answer:** D
+
+## Dataset Statistics
+
+- Total questions: ~1.6M+
+- Number of datasets used: 3
+- Categories: 5
+
+## Data Generation Pipeline
+
+HandVQA is generated using a deterministic pipeline:
+
+1. **Pose Descriptor Extraction**
+   - Compute angles, distances, and relative positions from 3D joints
+
+2. **Discretization**
+   - Convert continuous values into categories (e.g., bent, straight)
+
+3. **Sentence Generation**
+   - Fill structured templates
+
+4. **MCQ Formation**
+   - Generate correct + distractor answers
+  
+
+## Intended Uses
+
+- Benchmarking spatial reasoning in VLMs
+- Training spatially-aware multimodal models
+- Evaluating hallucination in pose understanding
+- Studying geometry-grounded reasoning
+
+## Evaluation Metrics
+
+- Accuracy
+- Mean Absolute Error (MAE) for ordinal tasks (angle, distance)
+
+HandVQA evaluates whether models truly understand spatial geometry rather than relying on language priors.
+
+## Links
+
+- Project page: https://kcsayem.github.io/handvqa/
+- Paper: coming soon.
+- Code: coming soon.
+
+## Citation
+coming soon