Update README.md

README.md

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 The dataset used in this study is designed to evaluate and analyze multi-object hallucination by leveraging existing panoptic segmentation datasets. Specifically, it includes data from MSCOCO-Panoptic and ADE20K, ensuring access to diverse objects and their instance-level semantic annotations. 
 For more information, please visit [Multi-Object Hallucination](https://multi-object-hallucination.github.io).
 
+## Dataset Construction
+
+The dataset is divided into several subsets based on the distribution of object classes within each image at test time. This division allows for a more granular analysis of how different distributions affect the hallucination behavior of large vision-language models (LVLMs).
+
+- **Homogeneous**: All tested objects in an image belong to the same class (e.g., AAAAA).
+- **Heterogeneous**: All tested objects in an image belong to different classes (e.g., ABCDE).
+- **In-the-Wild**: A mixed distribution where the tested objects are randomly chosen and ordered within each image.
+- **Adversarial**: A subset designed to challenge the models with difficult object distributions.
+
+
 ## Dataset Statistics
 ### Training Data Statistics
 
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     - name: data_source
       dtype: string
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-
-### Dataset Sources [optional]
-
-<!-- Provide the basic links for the dataset. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
 
-<!-- Address questions around how the dataset is intended to be used. -->
-
-### Direct Use
-
-<!-- This section describes suitable use cases for the dataset. -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
 
 ## Dataset Structure