Update README.md

README.md

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+---
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+# USB: A Unified Summarization Benchmark Across Tasks and Domains
+
+This benchmark contains labeled datasets for 8 text summarization based tasks given below. 
+The labeled datasets are created by collecting manual annotations on top of Wikipedia articles from 6 different domains.
+
+
+
+|Task                |Description                          |Code snippet                         |
+|----------------|-------------------------------|-----------------------------|
+| Extractive Summarization |  Highlight important sentences in the source article | `load_dataset("kundank/usb","extractive_summarization")` |
+| Abstractive Summarization | Generate a summary of the source | `load_dataset("kundank/usb","abstractive_summarization")` |
+| Topic-based Summarization |  Generate a summary of the source focusing on the given topic | `load_dataset("kundank/usb","topicbased_summarization")` |
+| Multi-sentence Compression | Compress selected sentences into a one-line summary | `load_dataset("kundank/usb","multisentence_compression")` |
+| Evidence Extraction | Surface evidence from the source for a summary sentence | `load_dataset("kundank/usb","evidence_extraction")` |
+| Factuality Classification | Predict the factual accuracy of a summary sentence with respect to provided evidence | `load_dataset("kundank/usb","factuality_classification")` |
+| Unsupported Span Prediction | Identify spans in a summary sentence which are not substantiated by the provided evidence | `load_dataset("kundank/usb","unsupported_span_prediction")` |
+| Fixing Factuality | Rewrite a summary sentence to remove any factual errors or unsupported claims, with respect to provided evidence | `load_dataset("kundank/usb","fixing_factuality")` |
+
+
+Additionally, to load the full set of collected annotations which were leveraged to make the labeled datasets for above tasks, use the command:  ``load_dataset("kundank/usb","all_annotations")``
+
+
+More details can be found in the paper: https://aclanthology.org/2023.findings-emnlp.592/
+
+If you use this dataset, please cite it as below:
+
+```
+@inproceedings{krishna-etal-2023-usb,
+    title = "{USB}: A Unified Summarization Benchmark Across Tasks and Domains",
+    author = "Krishna, Kundan  and
+      Gupta, Prakhar  and
+      Ramprasad, Sanjana  and
+      Wallace, Byron  and
+      Bigham, Jeffrey  and
+      Lipton, Zachary",
+    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2023",
+    year = "2023",
+    pages = "8826--8845"
+}
+```