Restore correct dataset card (v0, 10K<n<100K, full metadata)

README.md

@@ -1,5 +1,5 @@
 ---
-pretty_name: MathNet — Olympiad Math Reasoning & Retrieval (Preview)
+pretty_name: "MathNet v0 — Olympiad Math Reasoning & Retrieval"
 license: cc-by-4.0
 task_categories:
   - question-answering
@@ -31,7 +31,7 @@ tags:
   - multimodal
   - retrieval
   - iclr-2026
-  - preview
+  - v0
 size_categories:
   - 10K<n<100K
 configs:
@@ -88,14 +88,14 @@ configs:
     data_files:
       - split: train
         path: data/Croatia/train-*.parquet
-  - config_name: Czech_Republic
-    data_files:
-      - split: train
-        path: data/Czech_Republic/train-*.parquet
   - config_name: Czech-Polish-Slovak_Mathematical_Match
     data_files:
       - split: train
         path: data/Czech-Polish-Slovak_Mathematical_Match/train-*.parquet
+  - config_name: Czech_Republic
+    data_files:
+      - split: train
+        path: data/Czech_Republic/train-*.parquet
   - config_name: Estonia
     data_files:
       - split: train
@@ -188,6 +188,10 @@ configs:
     data_files:
       - split: train
         path: data/Philippines/train-*.parquet
+  - config_name: Portuguese_Language_Countries_Olympiad_OMCPLP
+    data_files:
+      - split: train
+        path: data/Portuguese_Language_Countries_Olympiad_OMCPLP/train-*.parquet
   - config_name: Romania
     data_files:
       - split: train
@@ -271,22 +275,16 @@ configs:
 ---
 
 <div align="center">
-
-<img src="assets/title_w_logo_dark.png" alt="MathNet" width="960"/>
-
-<a href="https://mathnet.mit.edu"><img alt="Website" src="https://img.shields.io/badge/website-mathnet.mit.edu-0d056f"></a>
-<a href="https://arxiv.org/abs/2604.18584"><img alt="ICLR 2026" src="https://img.shields.io/badge/ICLR-2026-b31b1b"></a>
-
-**Shaden Alshammari**<sup>1\*</sup> &ensp; **Kevin Wen**<sup>1\*</sup> &ensp; **Abrar Zainal**<sup>3\*</sup> &ensp; **Mark Hamilton**<sup>1</sup>
-**Navid Safaei**<sup>4</sup> &ensp; **Sultan Albarakati**<sup>2</sup> &ensp; **William T. Freeman**<sup>1†</sup> &ensp; **Antonio Torralba**<sup>1†</sup>
-
-<sup>1</sup>MIT &ensp; <sup>2</sup>KAUST &ensp; <sup>3</sup>HUMAIN &ensp; <sup>4</sup>Bulgarian Academy of Sciences &ensp; <sub>\*† equal contribution</sub>
-
+<img src="assets/title_w_logo_light.png" alt="MathNet" width="960"/>
+<img src="assets/overview.png" alt="MathNet overview: large-scale multilingual data, high-quality solutions, diverse topics, and three evaluation tasks" width="100%"/>
+  <a href="https://arxiv.org/abs/2604.18584"><img alt="ICLR 2026" src="https://img.shields.io/badge/ICLR-2026-b31b1b"></a>
+  <a href="https://mathnet.mit.edu"><img alt="Website" src="https://img.shields.io/badge/website-mathnet.mit.edu-0d056f"></a>
 </div>
 
----
-[Quick Start](#quick-start) · [Overview](#overview) · [Tasks](#three-benchmark-tasks) · [Comparison](#how-mathnet-compares-to-existing-math-benchmarks) · [Dataset Stats](#dataset-at-a-glance) · [Data Sources](#data-sources) · [Pipeline](#data-pipeline) · [Schema](#schema) · [License](#license) · [Citation](#citation)
+[Quick Start](#quick-start) · [Overview](#overview) · [Tasks](#three-benchmark-tasks) · [Comparison](#how-mathnet-compares-to-existing-math-benchmarks) · [Dataset Stats](#dataset-at-a-glance) · [Data Sources](#data-sources) · [Pipeline](#data-pipeline) · [Schema](#schema) · [License](#license) · [Citation](#citation) 
 
+> **This is MathNet v0.** A larger version **v1** will be uploaded by **Friday, April 24, 2026** (more countires, problems and richer metadata). Schema is stable but field values may be revised in v1.
+ 
 ---
 ## Quick start
 
@@ -301,16 +299,13 @@ arg  = load_dataset("ShadenA/MathNet", "Argentina", split="train")
 apmo = load_dataset("ShadenA/MathNet", "Asia_Pacific_Mathematics_Olympiad_APMO", split="train")
 
 row = ds[0]
-print(row["competition"], row["year"], row["country"])
+print(row["competition"], row["country"])
 print(row["problem_markdown"])
 for img in row["images"]:
     img.show()  # PIL image — renders inline in the HF viewer
 ```
 
 ## Overview
-
-<img src="assets/overview.png" alt="MathNet overview: large-scale multilingual data, high-quality solutions, diverse topics, and three evaluation tasks" width="100%"/>
-
 Mathematical problem solving remains a challenging test of reasoning for large language and multimodal models, yet existing benchmarks are limited in size, language coverage, and task diversity. We introduce **MathNet**, a high-quality, large-scale, multimodal, and multilingual dataset of Olympiad-level math problems together with a benchmark for evaluating mathematical reasoning in generative models **and** mathematical retrieval in embedding-based systems.
 
 MathNet spans **47 countries**, **17 languages**, and **two decades** of competitions, comprising **30,676 expert-authored problems with solutions** across diverse domains. Alongside the core dataset, we construct a retrieval benchmark of mathematically equivalent and structurally similar problem pairs curated by human experts.
@@ -383,45 +378,40 @@ Extracting aligned problem–solution pairs from a heterogeneous corpus of mathe
 2. **GPT-4.1-as-judge** — GPT-4.1 compares page screenshots against the extracted pair to catch OCR errors, incorrect figure associations, and incomplete solutions.
 3. **Human expert review** — low-confidence cases are manually reviewed by annotators. A pair is retained only if all three mechanisms agree.
 
-Provenance (source booklet, page numbers, authors where given) is preserved on every problem.
+Provenance (source booklet, authors where given) is preserved on every problem.
+
+## What v0 contains
 
-## What this preview contains
+This is the **v0 drop** of MathNet — the first complete public release:
 
-A **diverse 100-problem slice** sampled round-robin across countries, prioritizing problems with figures so the multimodal path is visible end-to-end. Images are **embedded** in the parquet as HF `Image()` features — they render inline in the dataset viewer and decode to PIL on load.
+- **27,817 problems** across **58 country / regional-body configs**
+- **5,148 problems with figures**, totalling **7,541 images** embedded inline as HF `Image()` features (they render in the viewer and decode to PIL on load)
+- All image references in problem and solution markdown are rewritten to the uniform `![](attached_image_N.png)` convention and the corresponding bytes ship in the `images` column in the same order
+- Default `all` config opens with a curated head of ~120 country-diverse, figure-rich problems so the dataset viewer preview is visually representative; the remainder of `all` is shuffled
+
+A more refined **v1** — larger, with improved extraction, deduplication, and metadata — will be uploaded by **Friday, April 24, 2026**.
 
 ## Schema
 
 | Column | Type | Notes |
 |---|---|---|
-| `unique_id` | string | Stable SHA-256 content hash |
-| `country` | string | Country / regional body of origin |
+| `id` | string | Short 4-char base36 identifier, stable across rebuilds |
+| `country` | string | Country or regional body of origin |
 | `competition` | string | e.g. `IMO 2023`, `Cono Sur Mathematical Olympiad` |
-| `year` | int32 | Year of competition |
-| `section` | string\|null | Day / round / level |
-| `problem_number` | string | As printed in the booklet |
-| `problem_markdown` | string | Problem statement (Markdown + LaTeX) |
-| `solutions_markdown` | list&lt;string&gt; | Official / provided solutions |
-| `answers_markdown` | list&lt;string&gt; | Final answers when stated separately |
-| `topics` | list&lt;list&lt;string&gt;&gt; | Hierarchical tags |
-| `topics_flat` | list&lt;string&gt; | Joined `A > B > C` strings |
+| `problem_markdown` | string | Problem statement (Markdown + LaTeX) with `![](attached_image_N.png)` refs |
+| `solutions_markdown` | list&lt;string&gt; | Official / provided solutions, one entry per solution |
+| `topics_flat` | list&lt;string&gt; | Hierarchical topic paths joined as `A > B > C` |
 | `language` | string | Source booklet language |
-| `source_booklet` | string | Booklet id (e.g. `ARG_2003`) |
 | `booklet_source` | string | Upstream collection label |
-| `has_images` | bool | Whether the problem cites figures |
-| `num_images` | int32 | Count of referenced figures |
-| `images` | list&lt;Image&gt; | Inlined bytes, decoded to PIL |
-| `natural_language_description` | string\|null | LLM-assisted NL rephrasing |
-| `main_ideas` | list&lt;string&gt; | LLM-assisted key solution ideas |
-| `final_answer` | string\|null | LLM-extracted final answer |
-| `problem_type` | string\|null | `proof`, `answer`, `proof and answer`, … |
-| `metadata_confidence` | float32 | Self-rated confidence of LLM metadata |
-| `original_problem_markdown` | string\|null | Pre-normalization text |
-
-> The enriched fields (`natural_language_description`, `main_ideas`, `final_answer`, `problem_type`, `metadata_confidence`) are **LLM-assisted** and not fully human-audited in the preview. Treat them as convenience annotations, not ground truth.
+| `images` | list&lt;Image&gt; | Inlined figure bytes, decoded to PIL; positions align with `attached_image_N.png` refs in the markdown |
+| `problem_type` | string\|null | `proof only`, `answer only`, `proof and answer` — LLM-assisted |
+| `final_answer` | string\|null | LLM-extracted final answer for answer-bearing problems |
+
+> `problem_type` and `final_answer` are **LLM-assisted** and not fully human-audited in v0. Treat them as convenience annotations, not ground truth.
 
 ## Configs / splits
 
-One config per **country or regional body** plus a default `all` config unioning everything. Each config has a single `train` split — this is a preview, not the train/test partitioning of `MathNet-Solve` (which is `train: 23,776`, `test: 6,400`, `test-hard: 500` in the full release).
+One config per **country or regional body** (58 total) plus a default `all` config unioning everything. Each config has a single `train` split — this is the public v0 release, not the train/test partitioning of `MathNet-Solve` (which is `train: 23,776`, `test: 6,400`, `test-hard: 500` in the paper release).
 
 ## Intended uses & limitations
 
@@ -429,12 +419,12 @@ One config per **country or regional body** plus a default `all` config unioning
 
 **Caveats.**
 - **Not contamination-clean.** Olympiad problems are indexed widely; assume leakage when evaluating pretrained models.
-- **Preview schema may change** before the full release.
+- **v0 field values may be revised in v1** (improved extraction / dedup / metadata).
 - **LLM-assisted metadata is imperfect.**
 
 ## License
 
-With the kind support of IMO President Gregor Dolinar, we reached out to the leaders of all participating countries and obtained their permission to share this dataset publicly. Where a country or contest organization asserts its own copyright, that copyright is retained and takes precedence — see `competition`, `country`, and `source_booklet` on each row. For all remaining problems where no explicit copyright was asserted, the dataset is released under **[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)**.
+With the kind support of IMO President Gregor Dolinar, we reached out to the leaders of all participating countries and obtained their permission to share this dataset publicly. Where a country or contest organization asserts its own copyright, that copyright is retained and takes precedence — see `competition`, `country`, and `booklet_source` on each row. For all remaining problems where no explicit copyright was asserted, the dataset is released under **[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)**.
 
 In short: use freely, cite the paper, and respect any explicit rights claimed by the original national team.
 
@@ -462,3 +452,4 @@ If you are a rightsholder with a concern, please open an issue or email [shaden@
 - ✉️ **Contact:** [shaden@mit.edu](mailto:shaden@mit.edu)
 
 <p align="center"><sub>© 2026 Massachusetts Institute of Technology · MathNet · ICLR 2026</sub></p>
+