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README.md

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+# MuLD
+> MuLD: The Multitask Long Document Benchmark
+
+MuLD (Multitask Long Document Benchmark) is a set of 6 NLP tasks where the inputs consist of at least 10,000 words. The benchmark covers a wide variety of task types including translation, summarization, question answering, and classification. Additionally there is a range of output lengths from a single word classification label all the way up to an output longer than the input text.
+
+- **Repository:** https://github.com/ghomasHudson/muld
+- **Paper:** https://arxiv.org/abs/2202.07362
+
+### Supported Tasks and Leaderboards
+
+The 6 MuLD tasks consist of:
+
+
+### Dataset Structure
+The data is presented in a text-to-text format where each instance contains a input string, output string and (optionally) json encoded metadata.
+```
+{'input: 'Who was wearing the blue shirt? The beginning...', 'output': ['John'], 'metadata': ''}
+```
+
+### Data Fields
+- `input`: a string which has a differing structure per task but is presented in a unified format
+- `output`: a list of strings where each is a possible answer. Most instances only have a single answer, but some such as narrativeQA and VLSP may have multiple.
+- `metadata`: Additional metadata which may be helpful for evaluation. In this version, only the OpenSubtitles task contains metadata (for the ContraPro annotations).
+
+### Data Splits
+Each tasks contains different splits.