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