Update README.md

README.md

@@ -11,7 +11,49 @@ As of this writing, ours is the only public dataset which is both fully annotate
 
 It is designed to be used for controlled experiments with vision-language models.
 
-For more details on our dataset, please refer to the accompanying paper.
+## What is in JANuS?[](#what-is-in-JANuS)
+
+JANuS provides metadata and image links for four new training datasets; all of these datasets are designed for evaluation on a subset of 100 classes chosen from ImageNet-1000. 
+
+Each dataset in JANuS is either a subset or a superset of an existing dataset, and each is fully captioned and fully labeled, either using annotated or synthetic labels.
+
+For additional details on our methodology for gathering JANuS, as well as explanations of terms like "subset matching", please refer to our paper.
+
+1.  **ImageNet-100:** A superset of ImageNet with over 50,000 newly
+    annotated samples, including flickr-captions and blip-captions.
+
+2.  **OpenImages-100:** A subset of OpenImages with new mappings from
+    OpenImages to ImageNet classes, restored original flickr-captions,
+    and new BLIP-captions.
+
+3.  **LAION-100:** A subset of LAION-15m with samples selected via
+    subset matching.
+
+4.  **YFCC-100:** A subset of YFCC-15m with samples selected via subset
+    matching.
+
+## Training on JANuS[](#training-on-JANuS)
+
+JANuS is designed to allow researchers to easily compare the effects of different labeling strategies on model performance. As such, every subset of JANuS includes at least two labeling sources.
+
+* **idx** labels are integers, mapping to [ImageNet-1k class labels](https://deeplearning.cms.waikato.ac.nz/user-guide/class-maps/IMAGENET/)
+* **caption** labels are natural language captions (usually in English), and are suitable for training VL-loss models like [CLIP](https://openai.com/blog/clip/)
+
+For YFCC-100 and LAION-100, the idx labels are synthetic, and are generated via a simple subset matching strategy. For ImageNet-100 and OpenImages-100, the idx labels are annotated by humans.
+
+YFCC-100, ImageNet-100 and OpenImages-100 contain captions sourced from Flickr. LAION-100 contains captions sourced from alt-text descriptions. 
+
+Additional labeling sources are available for some of the datasets in JANuS; please reference our paper for a reference key for all of the columns in the spreadsheets.
+
+[VL Hub](https://github.com/penfever/vlhub/), a framework for vision language model training, can be used to reproduce the experiments in our paper.
+
+## Evaluation on JANuS[](#evaluation-on-JANuS)
+
+Evaluation methods for JANuS models are the same as those for ImageNet models, except that we evaluate only on a subset of all ImageNet classes.
+
+For details on which classes are included in JANuS, please see metadata/in100_classes.txt in this repo.
+
+## Citations
 
 If you find our dataset useful, please cite our paper --