Add DaEdiTikZ dataset card

README.md

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+---
+license: apache-2.0
+pipeline_tag: image-text-to-text
+task_categories:
+- image-to-text
+- text-generation
+language:
+- en
+size_categories:
+- 100K<n<1M
+tags:
+- tikz
+- latex
+- code-generation
+- scientific-figures
+- image-editing
+- multimodal
+---
+
+# Dataset Card for DaEdiTikZ
+
+DaEdiTikZ is a dataset of realistic scientific-figure editing trajectories for TikZ/LaTeX used to train **EdiTikZ-4B**, **EdiTikZ-4B-RL**, **EdiTikZ-9B**, and **EdiTikZ-9B-RL**.
+
+Each record pairs two source TikZ programs/rendered figures mined from **ArXiv**, **GitHub**, and **TeXStackExchange** revision trajectories, and natural-language edit instructions generated by **Qwen3.6-27B** in both directions. It supports the task of generating an edited TikZ program from a source figure and an edit instruction.
+
+The release contains 106,358 redistributable figure pairs. Each pair provides two directional training instances. Image `i` to image `j` with the forward instruction, and image `j` to image `i` with the backward instruction, resulting in 212,716 samples.
+
+## Dataset fields
+
+Each row contains one bidirectional figure pair:
+
+- `group_id`: source-specific revision group identifier
+- `source`: origin category (`arxiv`, `github`, or `tex`)
+- `similarity_score`: cosine similarity of the paired rendered figures (between 0.95 and 0.9999)
+- `file_id_i`, `tikz_code_i`, `image_i`: identifier, full source, and rendered PNG for the first figure
+- `file_id_j`, `tikz_code_j`, `image_j`: identifier, full source, and rendered PNG for the second figure
+- `edit_instruction_forward`: detailed changes describing `i → j`
+- `edit_instruction_backward`: detailed changes describing `j → i`
+
+## Installation
+
+```bash
+pip install datasets
+```
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset_id = "nllg/DaEdiTikZ"
+
+ds = load_dataset(dataset_id, split="train")
+
+pair = ds[0]
+
+print(pair["group_id"], pair["source"], pair["similarity_score"])
+
+# Forward editing task: image_i + forward instruction -> tikz_code_j
+source_image = pair["image_i"]
+instruction = pair["edit_instruction_forward"]
+target_tikz = pair["tikz_code_j"]
+
+# Reverse direction: image_j + backward instruction -> tikz_code_i
+reverse_image = pair["image_j"]
+reverse_instruction = pair["edit_instruction_backward"]
+reverse_target_tikz = pair["tikz_code_i"]
+```