Update README.md

README.md

@@ -45,3 +45,60 @@ configs:
   - split: test
     path: data/test-*
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+
+# WikiSplit++
+
+This dataset is the HuggingFace version of WikiSplit++.  
+WikiSplit++ enhances the original WikiSplit by applying two techniques: filtering through NLI classification and sentence-order reversing, which help to remove noise and reduce hallucinations compared to the original WikiSplit.  
+The preprocessed WikiSplit dataset that formed the basis for this can be found [here](https://huggingface.co/datasets/cl-nagoya/wikisplit).
+
+## Usage
+
+```python
+import datasets as ds
+
+dataset: ds.DatasetDict = ds.load_dataset("cl-nagoya/wikisplit-pp", split="train")
+
+print(dataset)
+
+# DatasetDict({
+#     train: Dataset({
+#         features: ['id', 'complex', 'simple_reversed', 'simple_tokenized', 'simple_original', 'entailment_prob', 'split'],
+#         num_rows: 504375
+#     })
+#     validation: Dataset({
+#         features: ['id', 'complex', 'simple_reversed', 'simple_tokenized', 'simple_original', 'entailment_prob', 'split'],
+#         num_rows: 63065
+#     })
+#     test: Dataset({
+#         features: ['id', 'complex', 'simple_reversed', 'simple_tokenized', 'simple_original', 'entailment_prob', 'split'],
+#         num_rows: 62993
+#     })
+# })
+```
+
+### Data Fields
+
+- id: The ID of the data (note that it is not compatible with the existing WikiSplit)
+- complex: A complex sentence
+- simple_reversed: Simple sentences with their order reversed
+- simple_tokenized: A list of simple sentences split by [PySBD](https://github.com/nipunsadvilkar/pySBD), not reversed in order (often consists of 2 elements)
+- simple_original: Simple sentences in their original order
+- entailment_prob: The average probability that each simple sentence is classified as an entailment according to the complex sentence. [DeBERTa-xxl](https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli) is used for the NLI classification.
+- split: Indicates which split (train, val, or tune) this data belonged to in the original WikiSplit dataset
+
+## Paper
+
+Tsukagoshi et al., [WikiSplit++: Easy Data Refinement for Split and Rephrase](https://arxiv.org/abs/2404.09002), LREC-COLING 2024.
+
+## Abstract
+
+The task of Split and Rephrase, which splits a complex sentence into multiple simple sentences with the same meaning, improves readability and enhances the performance of downstream tasks in natural language processing (NLP).  
+However, while Split and Rephrase can be improved using a text-to-text generation approach that applies encoder-decoder models fine-tuned with a large-scale dataset, it still suffers from hallucinations and under-splitting.  
+To address these issues, this paper presents a simple and strong data refinement approach.   
+Here, we create WikiSplit++ by removing instances in WikiSplit where complex sentences do not entail at least one of the simpler sentences and reversing the order of reference simple sentences.  
+Experimental results show that training with WikiSplit++ leads to better performance than training with WikiSplit, even with fewer training instances.  
+In particular, our approach yields significant gains in the number of splits and the entailment ratio, a proxy for measuring hallucinations.  
+
+## License
+