Update README.md

README.md

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+# MMCricBench 🏏
+**Multimodal Cricket Scorecard Benchmark for VQA (Evaluation-Only)**
+
+MMCricBench evaluates **Large Vision-Language Models (LVLMs)** on **numerical reasoning**, **cross-lingual understanding**, and **multi-image reasoning** over semi-structured cricket scorecard images. It includes English and Hindi scorecards; all questions/answers are in English.
+
+**Dataset:** https://huggingface.co/datasets/DIALab/MMCricBench  
+**Status:** Evaluation-only (**no train/val splits**)
+
+---
+
+## Overview
+- **Images:** 1,463 synthetic scorecards (PNG)  
+  - 822 single-image scorecards  
+  - 641 multi-image scorecards
+- **QA pairs:** 1,500 (English)
+- **Reasoning categories:**  
+  - **C1** – Direct retrieval & simple inference  
+  - **C2** – Basic arithmetic & conditional logic  
+  - **C3** – Multi-step quantitative reasoning (often across images)
+
+---
+
+## Files / Splits
+We provide two evaluation splits:
+- `test_single` — single-image questions  
+- `test_multi` — multi-image questions
+
+> If you keep a single JSONL (e.g., `test_all.jsonl`), use a **list** for `images` in every row. Single-image rows should have a one-element list. On the Hub, we expose two test splits.
+
+---
+
+## Data Schema
+Each row is a JSON object:
+
+| Field      | Type                | Description                                  |
+|------------|---------------------|----------------------------------------------|
+| `id`       | `string`            | Unique identifier                            |
+| `images`   | `list[string]`      | Paths to one or more scorecard images        |
+| `question` | `string`            | Question text (English)                      |
+| `answer`   | `string`            | Ground-truth answer (canonicalized)          |
+| `category` | `string` (`C1/C2/C3`)| Reasoning category                           |
+| `subset`*  | `string` (`single/multi`) | Optional convenience field              |
+
+**Example (single-image):**
+```json
+{"id":"english-single-9","images":["English-apr/single_image/1198246_2innings_with_color1.png"],"question":"Which bowler has conceded the most extras?","answer":"Wahab Riaz","category":"C2","subset":"single"}
+```
+
+## Loading & Preview
+
+### Load from the Hub (two-split layout)
+```python
+from datasets import load_dataset
+
+# Loads: DatasetDict({'test_single': ..., 'test_multi': ...})
+ds = load_dataset("DIALab/MMCricBench")
+print(ds)
+
+# Peek a single-image example
+ex = ds["test_single"][0]
+print(ex["id"])
+print(ex["question"], "->", ex["answer"])
+
+# Preview images (each example stores a list of PIL images)
+from IPython.display import display
+for img in ex["images"]:
+    display(img)
+```
+
+## Baseline Results (from the paper)
+
+Accuracy (%) on MMCricBench by split and language.
+
+| Model             | #Params | Single-EN (Avg) | Single-HI (Avg) | Multi-EN (Avg) | Multi-HI (Avg) |
+|-------------------|:------:|:---------------:|:---------------:|:--------------:|:--------------:|
+| SmolVLM           | 500M   | 19.2 | 19.0 | 11.8 | 11.6 |
+| Qwen2.5VL         | 3B     | 40.2 | 33.3 | 31.2 | 22.0 |
+| LLaVA-NeXT        | 7B     | 28.3 | 26.6 | 16.2 | 14.8 |
+| mPLUG-DocOwl2     | 8B     | 20.7 | 19.9 | 15.2 | 14.4 |
+| Qwen2.5VL         | 7B     | 49.1 | 42.6 | 37.0 | 32.2 |
+| InternVL-2        | 8B     | 29.4 | 23.4 | 18.6 | 18.2 |
+| Llama-3.2-V       | 11B    | 27.3 | 24.8 | 26.2 | 20.4 |
+| **GPT-4o**        | —      | **57.3** | **45.1** | **50.6** | **43.6** |
+
+*Numbers are exact-match accuracy (higher is better). For C1/C2/C3 breakdowns, see Table 3 (single-image) and Table 5 (multi-image) in the paper.* :contentReference[oaicite:0]{index=0} :contentReference[oaicite:1]{index=1}
+