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README.md

@@ -1,8 +1,43 @@
 ---
 task_categories:
-- question-answering
+- visual-question-answering
+- document-question-answering
 language:
 - en
-size_categories:
-- 1M<n<10M
----
+tags:
+- multimodal
+- benchmark
+- document-understanding
+configs:
+- config_name: default
+  data_files:
+  - split: val
+    path: "val.parquet"
+---
+
+# DocVQA2026 | ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains
+
+Building upon previous DocVQA benchmarks, this evaluation dataset introduces challenging reasoning questions over a diverse collection of documents spanning eight domains, including business reports, scientific papers, slides, posters, maps, comics, infographics, and engineering drawings.
+
+By expanding coverage to new document domains and introducing richer question types, this benchmark seeks to push the boundaries of multimodal reasoning and promote the development of more general, robust document understanding models.
+
+
+## Results
+
+## Dataset Structure
+
+The dataset consists of:
+1.  **Images:** High-resolution PNG renders of document pages located in the `images/` directory.
+2.  **Metadata:** A Parquet file (`validation.parquet`) containing the questions, answers, and references to the image paths.
+
+### Schema
+
+| Field | Type | Description |
+| :--- | :--- | :--- |
+| `id` | `string` | Unique identifier for the question (e.g., `slide_1_q1`). |
+| `doc_id` | `string` | Identifier for the document context. |
+| `image_paths` | `list[string]` | A list of relative paths to all pages associated with the document. |
+| `question` | `string` | The visual question. |
+| `answer` | `string` | The ground truth answer. |
+| `doc_category` | `string` | The type of document (e.g., `science_paper`, `financial_report`). |
+