Update README.md

README.md

@@ -24,13 +24,13 @@ dataset_info:
     dtype: string
   splits:
   - name: test_open
-    num_bytes: 134659773.0
+    num_bytes: 134659773
     num_examples: 100
   - name: test_closed
-    num_bytes: 67549223.0
+    num_bytes: 67549223
     num_examples: 150
   download_size: 270416985
-  dataset_size: 202208996.0
+  dataset_size: 202208996
 - config_name: Domestic Robot
   features:
   - name: domain
@@ -55,13 +55,13 @@ dataset_info:
     dtype: string
   splits:
   - name: test_open
-    num_bytes: 91702060.0
+    num_bytes: 91702060
     num_examples: 100
   - name: test_closed
-    num_bytes: 177827577.0
+    num_bytes: 177827577
     num_examples: 200
   download_size: 105390299
-  dataset_size: 269529637.0
+  dataset_size: 269529637
 - config_name: Open-World Game
   features:
   - name: domain
@@ -86,13 +86,13 @@ dataset_info:
     dtype: string
   splits:
   - name: test_open
-    num_bytes: 16139511.0
+    num_bytes: 16139511
     num_examples: 117
   - name: test_closed
-    num_bytes: 19069366.0
+    num_bytes: 19069366
     num_examples: 141
   download_size: 34988721
-  dataset_size: 35208877.0
+  dataset_size: 35208877
 configs:
 - config_name: Autonomous Driving
   data_files:
@@ -112,4 +112,59 @@ configs:
     path: Open-World Game/test_open-*
   - split: test_closed
     path: Open-World Game/test_closed-*
+license: apache-2.0
+task_categories:
+- multiple-choice
+- visual-question-answering
+language:
+- en
+pretty_name: PCA-Bench
 ---
+
+<h1 align="center">PCA-Bench</h1>
+
+<p align="center">
+
+<a href="https://github.com/pkunlp-icler/PCA-EVAL">
+<img alt="Static Badge" src="https://img.shields.io/badge/Github-Online-white">
+</a>
+
+<a href="https://arxiv.org/abs/2310.02071">
+<img alt="Static Badge" src="https://img.shields.io/badge/Paper-PCAEVAL-red">
+
+<a href="https://huggingface.co/datasets/PCA-Bench/PCA-Bench-V1">
+<img alt="Static Badge" src="https://img.shields.io/badge/Datasets-HuggingFace-yellow">
+</a>
+</p>
+
+
+
+
+*PCA-Bench is an innovative benchmark for evaluating and locating errors in Multimodal LLMs when conducting embodied decision making tasks, specifically focusing on perception, cognition, and action.*
+
+
+## News
+- PCA-Bench-V1 is released in HuggingFace Datasets (Leaderboard Coming Soon).
+
+
+
+## Run Evaluation on Accuracy
+
+```python
+#pip install datasets
+from datasets import load_dataset
+dataset_ad = load_dataset("PCA-Bench/PCA-Bench-V1","Autonomous Driving")
+dataset_dr = load_dataset("PCA-Bench/PCA-Bench-V1","Domestic Robot")
+dataset_og = load_dataset("PCA-Bench/PCA-Bench-V1","Open-World Game")
+
+# use your model to inference on the test_open/close split with "question_prompt" and "image" given in the datasets and extract the answers.
+# compute the acc regarding the action groundtruth of open track. 
+
+```
+
+📢 For close track data, please follow [this file](https://github.com/pkunlp-icler/PCA-EVAL/blob/main/pca-eval/results/chatgpt_holmes_outputs/Autonomous%20Driving.json) to organize your model output. Submit **three JSON files** from different domains, along with your **model name** and **organization** to us via [email](mailto:[email protected]). Ensure you use the dataset's provided prompt as the default input for fair comparison (You should mention in the email if custom prompts were used).
+
+We will send the closed track PCA-Eval results of your model to you.
+
+## PCA Evaluation
+To run PCA-Evaluation yourself, please follow the guidelines in the github repo [PCA-EVAL](https://github.com/pkunlp-icler/PCA-EVAL).