Update README.md

README.md

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----
-license: apache-2.0
-dataset_info:
-  features:
-  - name: question
-    dtype: string
-  - name: verifiable_answer
-    dtype: string
-  - name: year
-    dtype: string
-  - name: grade
-    dtype: string
-  - name: full_answer
-    dtype: string
-  - name: solutions
-    list: string
-  - name: task_complexity
-    dtype: string
-  - name: olympiad
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 510955
-    num_examples: 331
-  download_size: 228445
-  dataset_size: 510955
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+---
+license: apache-2.0
+task_categories:
+- question-answering
+language:
+- ru
+pretty_name: T-math
+size_categories:
+- n<1K
+dataset_info:
+  features:
+  - name: question
+    dtype: string
+  - name: verifiable_answer
+    dtype: string
+  - name: year
+    dtype: string
+  - name: grade
+    dtype: string
+  - name: full_answer
+    dtype: string
+  - name: solutions
+    list: string
+  - name: task_complexity
+    dtype: string
+  - name: olympiad
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 510955
+    num_examples: 331
+  download_size: 228445
+  dataset_size: 510955
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+---
+
+
+# 🧮 T-Math
+**T-Math** is a dataset of Russian math olympiad problems created to assess the reasoning capabilities of large language models (LLMs) in mathematics.  
+It includes 331 problems from the [All-Russian School Olympiad](https://vos.olimpiada.ru/) and the [Moscow Olympiad](https://mos.olimpiada.ru) for high school students, covering the period from 1998 to 2025.  
+The tasks and their ground-truth answers were extracted automatically and subsequently verified by human assessors.
+
+Key features:
+- Challenging problems that require multi-step reasoning (median completion length for Qwen3-32B is 16K tokens), sourced from top-tier Russian olympiads
+- Easily verifiable: answers are numeric-only and checked using the `math_verify` library to compare mathematical expressions
+- Not yet saturated, even by frontier reasoning models such as Gemini 2.5 Pro and DeepSeek R1
+- Contains 331 samples — the largest Russian math olympiad-level benchmark — making it more statistically robust compared to smaller datasets like the 30-sample AIME benchmark
+
+
+## 📊 Evaluation Results
+
+|Model|pass@1|
+|--|--|
+|o4-mini-high|**0.73**|
+|DeepSeek-R1-0528|<ins>0.71</ins>|
+|Gemini-2.5-Pro|0.70|
+|Claude Sonnet 4|0.56|
+|T-pro-it-2.0|0.54|
+|Qwen3-32B|0.53|
+
+
+## 🗂️ Filtering procedure
+
+The text was extracted from PDFs using [Qwen/Qwen2.5-VL-72B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-72B-Instruct). Tasks, along with their ground-truth and verifiable (numeric) answers, were extracted via LLM calls.
+We filtered out invalid questions using an LLM based on the following criteria:
+- Tasks requiring multiple answers
+- Tasks without a single correct answer
+- Theorem-like tasks where the main goal is proving a statement, making automatic verification non-trivial
+- Tasks with non-numeric answers, to simplify answer comparison
+- Tasks that cannot be solved without access to an accompanying image
+
+Next, we removed tasks of moderate difficulty where Qwen3-8B achieved a 100% pass@16 rate, as they offer limited value for benchmarking reasoning.
+Finally, both the questions and the verifiable answers were manually reviewed by assessors to ensure consistency with the original sources.
+
+
+## 🛠️ How to use
+Add the following system prompt to guide the model to return the final answer in a \boxed{} tag, making it easier to parse:
+```
+Решите следующую математическую задачу эффективно и ясно. Последняя строка вашего ответа должна иметь следующий формат:
+'Таким образом, окончательный ответ: $\boxed{ОТВЕТ}$.' (без кавычек), где ОТВЕТ - это просто окончательное число или выражение, решающее задачу.
+Думайте шаг за шагом перед ответом.
+```
+
+You can then use the following code snippet with the math_verify library to compare mathematical expressions:
+```python
+from math_verify import LatexExtractionConfig, parse, verify
+from latex2sympy2_extended import NormalizationConfig
+
+
+def accuracy_reward(completion: str, solution: str) -> float:
+    """Reward function that checks if the completion matches the ground truth."""
+    # parse the gold solution (assumed to always succeed)
+    gold_parsed = parse(solution, extraction_mode="first_match")
+
+    # parse the model’s completion with the same LaTeX extraction settings
+    answer_parsed = parse(
+        completion,
+        extraction_config=[
+            LatexExtractionConfig(
+                normalization_config=NormalizationConfig(
+                    nits=False,
+                    malformed_operators=False,
+                    basic_latex=True,
+                    equations=True,
+                    boxed="all",
+                    units=True,
+                )
+            )
+        ],
+        extraction_mode="first_match",
+    )
+
+    # verify and return binary reward; on error, print and give 0.0
+    try:
+        return float(verify(gold_parsed, answer_parsed))
+    except Exception as e:
+        print(f"verify failed: {e}, answer: {answer_parsed}, gold: {gold_parsed}")
+        return 0.0
+
+
+```