Update README.md

README.md

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 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: category
-    dtype: string
-  - name: image
-    dtype: image
-  - name: reasoning
-    dtype: string
-  - name: scripts_gurmukhi_question
-    dtype: string
-  - name: scripts_gurmukhi_options
-    sequence: string
-  - name: scripts_gurmukhi_answer
-    dtype: string
-  - name: scripts_shahmukhi_question
-    dtype: string
-  - name: scripts_shahmukhi_options
-    sequence: string
-  - name: scripts_shahmukhi_answer
-    dtype: string
-  - name: scripts_roman_question
-    dtype: string
-  - name: scripts_roman_options
-    sequence: string
-  - name: scripts_roman_answer
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 541053211.0
-    num_examples: 375
-  download_size: 540957323
-  dataset_size: 541053211.0
-configs:
+pretty_name: Punjabi Multimodal Visual Reasoning (PuMVR)
+tags:
+- multimodal
+- visual-question-answering
+- multi-script
+- low-resource-language
+- punjabi
+- image-to-text
+- multiple-choice
+language: # Corrected from 'languages' (singular is required)
+- pa # ISO 639-1 code for Punjabi
+- en # English
+language_bcp47:
+- pa-Guru # Punjabi, Gurmukhi script
+- pa-Arab # Punjabi, Shahmukhi script (Perso-Arabic)
+- pa-Latn # Punjabi, Roman script (Latin)
+task_categories:
+- visual-question-answering
+- image-to-text
+- multiple-choice
+- question-answering
+license: cc-by-4.0
+configs: # Corrected from object/mapping to an array of objects
 - config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+multilinguality: multi-script
+annotations_creators:
+- human
+language_creators:
+- native-speakers
+size_categories:
+- 100M<X<1B
 ---
+
+# PuMVR: Punjabi Multimodal Visual Reasoning Benchmark
+
+## 🌟 Dataset Overview
+
+**PuMVR (Punjabi Multimodal Visual Reasoning)** is a novel benchmark designed to evaluate **script-dependent performance biases** in Vision-Language Models (VLMs). It addresses the critical gap that current VLM evaluations fail to test whether models are truly **multi-script**, a distinction vital for languages like Punjabi which are actively written in multiple scripts.
+
+The dataset features **375 unique image-text reasoning tasks** focused on Punjabi culture, history, and daily life. All instances are translated and rigorously validated across the three active Punjabi writing systems: **Gurmukhi (pa-Guru), Shahmukhi (pa-Arab), and Roman (pa-Latn)**.
+
+* **Total Instances:** 375
+* **Total Size:** 541 MB
+* **Language:** Punjabi (pa) with three distinct script variants.
+* **Target Models:** State-of-the-art VLMs
+  
+---
+
+## 📊 Dataset Structure and Statistics
+
+The dataset is organized into a single split (`train`) and is composed of image data and corresponding textual annotations stored in a JSON file.
+
+### Data Fields
+
+The dataset schema contains all necessary components for running multiple-choice VQA across three scripts:
+
+| Field Name | Data Type | Description |
+| :--- | :--- | :--- |
+| **`id`** | `string` | Unique identifier (e.g., `C1_001`). |
+| **`category`** | `string` | The specific task category (1 of 6). |
+| **`image`** | `Image` | The associated visual input (decoded from the file path). |
+| **`reasoning`** | `string` | Human-written explanation for the ground truth answer (in English). |
+| **`scripts_[script]_question`** | `string` | The reasoning question in the specified script. |
+| **`scripts_[script]_options`** | `list[string]`| 4 multiple-choice options in the specified script. |
+| **`scripts_[script]_answer`** | `string` | The single correct option in the specified script. |
+
+*(The `[script]` placeholder is one of: `gurmukhi`, `shahmukhi`, or `roman`.)*
+
+### Task Categories
+
+The 375 instances are distributed across 6 categories, ensuring a comprehensive test of multimodal script robustness:
+
+1.  **Visual Analogies:** Tests relational reasoning (e.g., Turban:Head :: Shoe:?).
+2.  **Cultural Object Recognition:** Tests knowledge of Punjabi-specific cultural items (e.g., *Phulkari*, musical instruments).
+3.  **Festival & Celebration Reasoning:** Tests cultural knowledge and temporal reasoning around regional events (e.g., *Lohri*).
+4.  **Architectural & Landmark Recognition:** Tests visual and geographic grounding of regional landmarks (e.g., Golden Temple).
+5.  **Text-in-Image Reasoning:** Tests cross-script OCR and multimodal comprehension, including scenarios where image text and question text scripts are mismatched.
+6.  **Abstract Visual-Linguistic Reasoning:** Tests basic spatial and logical reasoning with Punjabi language labels.
+
+---
+
+## ⚖️ Ethical and Legal Considerations
+
+### Licenses
+* **Data:** The PuMVR dataset is released under the **Creative Commons Attribution 4.0 International License (CC BY 4.0)**.
+* **Images:** Majority (approximately 95%) of the images are AI-generated (synthetic data) to ensure cultural specificity and clear licensing. The remaining images are sourced from public domain, Wikimedia Commons, and original photography. 
+
+### Data Creation and Validation
+The textual data was created and rigorously validated by a team of native speakers across both Indian and Pakistani Punjabi contexts to ensure **semantic equivalence** and **cultural appropriateness** across the Gurmukhi, Shahmukhi, and Roman scripts.
+
+### Limitations
+The dataset is highly focused on **Punjabi culture**, which introduces a domain-specific bias. The Romanization used reflects common digital usage but is not strictly standardized, mirroring real-world multi-script challenges.