Update README.md

README.md

@@ -13,6 +13,10 @@ pretty_name: ASyMOB
 
 # [ASyMOB: Algebraic Symbolic Mathematical Operations Benchmark](https://arxiv.org/abs/2505.23851)
 
+This dataset is associated with the paper ["ASyMOB: Algebraic Symbolic Mathematical Operations Benchmark"](https://arxiv.org/abs/2505.23851).
+
+## Abstract
+
 Large language models (LLMs) are rapidly approaching the level of proficiency in university-level symbolic mathematics required for applications in advanced science and technology. However, existing benchmarks fall short in assessing the core skills of LLMs in symbolic mathematics—such as integration, limits, differential equations, and algebraic simplification. 
 
 To address this gap, we introduce ASyMOB (pronounced Asimov, in tribute to the renowned author), a novel assessment framework focused exclusively on symbolic manipulation, featuring 17,092 unique math challenges, organized by similarity and complexity. ASyMOB enables analysis of LLM failure root-causes and generalization capabilities by comparing performance in problems that differ by simple numerical or symbolic "perturbations". 
@@ -25,6 +29,8 @@ Notably, the most advanced models (o4-mini, Gemini 2.5 Flash) demonstrate not on
 
 # ASyMOB Dataset Generation
 
+See the [ASyMOB code repository](https://github.com/RamanujanMachine/ASyMOB) for the data generation code and seed CSV.
+
 ASyMOB_Generation.py generates a diverse set of mathematical question variants from a seed CSV file. It leverages the `SymPy` library for symbolic mathematics to create various perturbations of original questions, including symbolic, numeric, and equivalence-based transformations. The generated questions are then saved to a JSON file.
 
 ## Usage