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README.md

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-Datasets:
-multi_document_summarization 
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-Tasks: 
-summarization-other-paper-abstract-generation
-Task Categories: 
-summarization
-Languages: 
-en
-Multilinguality: 
-monolingual
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@@ -69,8 +17,8 @@ task_categories:
 - summarization
 task_ids:
 - summarization-other-paper-abstract-generation
-paperswithcode_id: multi-xscience
-pretty_name: Multi-XScience
+paperswithcode_id: multi-document
+pretty_name: Multi-Document
 ---
 # Dataset Card for Multi-XScience
 ## Table of Contents
@@ -97,35 +45,25 @@ pretty_name: Multi-XScience
   - [Citation Information](#citation-information)
   - [Contributions](#contributions)
 ## Dataset Description
-- **Repository:** [Multi-XScience repository](https://github.com/yaolu/Multi-XScience)
-- **Paper:** [Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles](https://arxiv.org/abs/2010.14235)
+- **Repository:** [Multi-Document repository](https://github.com/arka0821/multi_document_summarization)
+- **Paper:** [Multi-Document: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles](https://arxiv.org/abs/2010.14235)
 ### Dataset Summary
-Multi-XScience, a large-scale multi-document summarization dataset created from scientific articles. Multi-XScience introduces a challenging multi-document summarization task: writing the related-work section of a paper based on its abstract and the articles it references.
+Multi-Document, a large-scale multi-document summarization dataset created from scientific articles. Multi-Document introduces a challenging multi-document summarization task: writing the related-work section of a paper based on its abstract and the articles it references.
 ### Supported Tasks and Leaderboards
 [More Information Needed]
 ### Languages
 The text in the dataset is in English
 ## Dataset Structure
 ### Data Instances
-{'abstract': 'Author(s): Kuperberg, Greg; Thurston, Dylan P. | Abstract: We give a purely topological definition of the perturbative quantum invariants of links and 3-manifolds associated with Chern-Simons field theory. Our definition is as close as possible to one given by Kontsevich. We will also establish some basic properties of these invariants, in particular that they are universally finite type with respect to algebraically split surgery and with respect to Torelli surgery. Torelli surgery is a mutual generalization of blink surgery of Garoufalidis and Levine and clasper surgery of Habiro.',
- 'aid': 'math9912167',
- 'mid': '1631980677',
- 'ref_abstract': {'abstract': ['This note is a sequel to our earlier paper of the same title [4] and describes invariants of rational homology 3-spheres associated to acyclic orthogonal local systems. Our work is in the spirit of the Axelrod–Singer papers [1], generalizes some of their results, and furnishes a new setting for the purely topological implications of their work.',
-   'Recently, Mullins calculated the Casson-Walker invariant of the 2-fold cyclic branched cover of an oriented link in S^3 in terms of its Jones polynomial and its signature, under the assumption that the 2-fold branched cover is a rational homology 3-sphere. Using elementary principles, we provide a similar calculation for the general case. In addition, we calculate the LMO invariant of the p-fold branched cover of twisted knots in S^3 in terms of the Kontsevich integral of the knot.'],
-  'cite_N': ['@cite_16', '@cite_26'],
-  'mid': ['1481005306', '1641082372']},
- 'related_work': 'Two other generalizations that can be considered are invariants of graphs in 3-manifolds, and invariants associated to other flat connections @cite_16 . We will analyze these in future work. Among other things, there should be a general relation between flat bundles and links in 3-manifolds on the one hand and finite covers and branched covers on the other hand @cite_26 .'}
+{"id": "n3ByHGrxH3bvfrvF", "docs": [{"id": "1394519630182457344", "text": "Clover Bio's COVID-19 vaccine candidate shows immune response against SARS-CoV-2 variants in mouse model https://t.co/wNWa9GQux5"}, {"id": "1398154482463170561", "text": "The purpose of the Vaccine is not to stop you from catching COVID 19. The vaccine introduces the immune system to an inactivated form of the SARS-CoV-2 coronavirus or a small part of it. This then equips the body with the ability to fight the virus better in case you get it. https://t.co/Cz9OU6Zi7P"}, {"id": "1354844652520792071", "text": "The Moderna mRNA COVID-19 vaccine appears to be effective against the novel, rapidly spreading variants of SARS-CoV-2.\nResearchers analysed blood samples from vaccinated people and monkeys- Both contained neutralising antibodies against the virus. \nPT1/2\n#COVID19vaccines #biotech https://t.co/ET1maJznot"}, {"id": "1340189698107518976", "text": "@KhandaniM Pfizer vaccine introduces viral surface protein which is constant accross SARS COV 2 variants into the body. Body builds antibodies against this protein, not any virus. These antibodies instructs macrophages &amp; T-Cells to attack &amp; destroy any COVID-19 v variant  at infection point"}, {"id": "1374368989581778945", "text": "@DelthiaRicks \" Pfizer and BioNTech\u2019s COVID-19 vaccine is an mRNA vaccine, which does not use the live virus but rather a small portion of the viral sequence of the SARS-CoV-2 virus to instruct the body to produce the spike protein displayed on the surface of the virus.\""}, {"id": "1353354819315126273", "text": "Pfizer and BioNTech Publish Results of Study Showing COVID-19 Vaccine Elicits Antibodies that Neutralize Pseudovirus Bearing the SARS-CoV-2 U.K. Strain Spike Protein in Cell Culture | Pfizer https://t.co/YXcSnjLt8C"}, {"id": "1400821856362401792", "text": "Pfizer-BioNTech's covid-19 vaccine elicits lower levels of antibodies against the SARS-CoV-2\u00a0Delta variant\u00a0(B.1.617.2), first discovered in India, in comparison to other variants, said a research published in\u00a0Lancet\u00a0journal.\n https://t.co/IaCMX81X3b"}, {"id": "1367252963190665219", "text": "New research from UNC-Chapel Hill suggests that those who have previously experienced a SARS-CoV-2 infection develop a significant antibody response to the first dose of mRNA-based COVID-19 vaccine.\nhttps://t.co/B4vR1KUQ0w"}, {"id": "1375949502461394946", "text": "Mechanism of a COVID-19 nanoparticle vaccine candidate that elicits a broadly neutralizing antibody response to SARS-CoV-2 variants  https://t.co/nc1L0uvtlI #bioRxiv"}, {"id": "1395428608349548550", "text": "JCI - Efficient maternal to neonatal transfer of antibodies against SARS-CoV-2 and BNT162b2 mRNA COVID-19 vaccine https://t.co/vIBcpPaKFZ"}], "summary": "The COVID-19 vaccine appears to be effective against the novel, rapidly spreading variants of SARS-CoV-2. Pfizer-BioNTech's COVID-19 vaccine use small portion of the viral sequence of the SARS-CoV-2 virus to equip the body with the ability to fight the virus better in case you get it."}
 ### Data Fields
-{`abstract`: text of paper abstract \
- `aid`: arxiv id \
- `mid`: microsoft academic graph id \
- `ref_abstract`: \
-   { \
-    `abstract`: text of reference paper (cite_N) abstract \
-    `cite_N`: special cite symbol, \
-    `mid`: reference paper's (cite_N) microsoft academic graph id \
-   }, \
- `related_work`: text of paper related work \
+{'id': text of paper abstract \
+ 'docs': document id \
+ [
+   'id': id of text \
+   'text': text data \
+ ]
+  'summary': summary text
  }
 ### Data Splits
 The data is split into a training, validation and test.
@@ -162,12 +100,12 @@ The data is split into a training, validation and test.
 ### Citation Information
 ```
 @article{lu2020multi,
-  title={Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles},
-  author={Lu, Yao and Dong, Yue and Charlin, Laurent},
+  title={Multi-Document: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles},
+  author={Arka Das, India},
   journal={arXiv preprint arXiv:2010.14235},
-  year={2020}
+  year={2022}
 }
 ```
 ### Contributions
-Thanks to [@arka0821] for adding this dataset.
+Thanks to [@arka0821] (https://github.com/arka0821/multi_document_summarization) for adding this dataset.