Update README.md

README.md

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----
-license: apache-2.0
-dataset_info:
-  features:
-  - name: question_id
-    dtype: string
-  - name: category
-    dtype: string
-  - name: cluster
-    dtype: string
-  - name: turns
-    list:
-    - name: content
-      dtype: string
-  splits:
-  - name: train
-    num_bytes: 251691
-    num_examples: 500
-  download_size: 154022
-  dataset_size: 251691
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+---
+license: apache-2.0
+dataset_info:
+  features:
+  - name: question_id
+    dtype: string
+  - name: category
+    dtype: string
+  - name: cluster
+    dtype: string
+  - name: turns
+    list:
+    - name: content
+      dtype: string
+  splits:
+  - name: train
+    num_bytes: 251691
+    num_examples: 500
+  download_size: 154022
+  dataset_size: 251691
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+---
+
+## Arena-Hard-Auto
+
+**Arena-Hard-Auto-v0.1** ([See Paper](https://arxiv.org/abs/2406.11939)) is an automatic evaluation tool for instruction-tuned LLMs. It contains 500 challenging user queries sourced from Chatbot Arena. We prompt GPT-4-Turbo as judge to compare the models' responses against a baseline model (default: GPT-4-0314). Notably, Arena-Hard-Auto has the highest *correlation* and *separability* to Chatbot Arena among popular open-ended LLM benchmarks ([See Paper](https://arxiv.org/abs/2406.11939)). If you are curious to see how well your model might perform on Chatbot Arena, we recommend trying Arena-Hard-Auto.
+
+Please checkout our GitHub repo on how to evaluate models using Arena-Hard-Auto and more information about the benchmark. 
+
+If you find this dataset useful, feel free to cite us!
+```
+@article{li2024crowdsourced,
+  title={From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline},
+  author={Li, Tianle and Chiang, Wei-Lin and Frick, Evan and Dunlap, Lisa and Wu, Tianhao and Zhu, Banghua and Gonzalez, Joseph E and Stoica, Ion},
+  journal={arXiv preprint arXiv:2406.11939},
+  year={2024}
+}
+```