Add link to paper

README.md

@@ -21,7 +21,8 @@ dataset_info:
   dataset_size: 1015823
 ---
 
-# SOTA fine-tuning by OpenAI
+A dataset of 76 Python programs taken from real Python open source projects (top 100 on GitHub), 
+where each program is a file that has exactly 1 vulnerability as detected by a particular static analyzer (Semgrep), used in the paper [Patched MOA: optimizing inference for diverse software development tasks](https://huggingface.co/papers/2407.18521).
 
 OpenAI used the [synth-vuln-fixes](https://huggingface.co/datasets/patched-codes/synth-vuln-fixes) and fine-tuned
 a new version of gpt-4o is now the SOTA on this benchmark. More details and code is available from their [repo.](https://github.com/openai/build-hours/tree/main/5-4o_fine_tuning)
@@ -72,8 +73,7 @@ technique like MOA can improve performance without fine-tuning.
 
 # Static Analysis Eval Benchmark
 
-A dataset of 76 Python programs taken from real Python open source projects (top 100 on GitHub), 
-where each program is a file that has exactly 1 vulnerability as detected by a particular static analyzer (Semgrep).
+
 
 You can run the `_script_for_eval.py` script to check the results.