Challenge: SciPar is a collection of parallel corpora created from openly available metadata of bachelor theses, master theses and doctoral dissertations hosted in institutional repositories, digital libraries and national archives.
Approach: They propose to harvest and process openly available metadata from repositories to extract bilingual titles and abstracts from scientific publications.
Outcome: The proposed corpora could be useful for cross-lingual plagiarism detection or adapting Machine Translation systems for translation of scientific texts and academic writing in general.

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A Large Parallel Corpus of Full-Text Scientific Articles (L18-1)

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Challenge: Scielo database contains articles from several research domains.
Approach: They propose to build a parallel corpus from Scielo in three languages: English, Portuguese, and Spanish.
Outcome: The proposed system outperforms other systems on scientific articles in English, Portuguese, and Spanish.
A Multilingual Parallel Corpora Collection Effort for Indian Languages (2020.lrec-1)

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Challenge: Currently, neural network based approaches for machine translation are data hungry and sentence-level aligned parallel pairs are the currency.
Approach: They propose to build sentence aligned parallel corpora across 10 Indian languages using online sources which have content shared across languages.
Outcome: The proposed corpora significantly extends existing resources that are either not large enough or are restricted to a specific domain (such as health).
Parallel Corpora for the Biomedical Domain (L18-1)

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Challenge: Existing corpora of parallel corporata are being used in the biomedical domain . MT is known to support readers' access to textual documents in a language other than their native language .
Approach: They propose to leverage parallel corpora to implement cross-lingual information retrieval or machine translation tools.
Outcome: The proposed corpus is being used in the biomedical task at the conference on machine translation (WMT'16 and WMT'17) it can be leveraged to provide access to health information in languages other than English.
Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages (2022.tacl-1)

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Challenge: We present Samanantar, the largest publicly available parallel corpora collection for Indic languages . based on existing corporative, there has been limited benefit for resource-poor languages despite the lack of parallel corporals and monolingual corporata.
Approach: They compile 12.4 million sentence pairs from existing corpora and mine 37.4 million from the Web.
Outcome: The proposed model outperforms existing models and benchmarks on public datasets.
A New Massive Multilingual Dataset for High-Performance Language Technologies (2024.lrec-main)

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Challenge: a new massive multilingual dataset is available for language modeling and machine translation training.
Approach: They present a massive multilingual dataset using web crawls from the Internet Archive and CommonCrawl . they use open-source software tools and high-performance computing to acquire, manage and process large corpora .
Outcome: The HPLT language resources is a massive multilingual dataset . it includes monolingual and bilingual corpora extracted from CommonCrawl and the Internet Archive . the results are published online at the journal journal cense4 .
Beyond Metadata: What Paper Authors Say About Corpora They Use (2021.findings-acl)

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Challenge: Currently, dataset retrieval relies almost exclusively on metadata provided by the publishers.
Approach: They propose to use metadata to extract review statements from scientific publications . they argue that a crucial piece of information is missing to inform the examination of search results .
Outcome: The proposed analysis is the first of its kind in the field of Natural Language Processing.
A Multilingual Dataset for Evaluating Parallel Sentence Extraction from Comparable Corpora (L18-1)

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Challenge: BUCC Shared Task aims to extract parallel sentences from comparable corporad . resulting corpus contains about 3.5 million distinct sentences in english, french, german, Russian, and Chinese .
Approach: They present challenges faced to build a parallel sentences dataset from comparable corporad . they emphasize issues faced to include Chinese as one of the languages .
Outcome: The 2017 BUCC Shared Task was a first for this task . the dataset contains 3.5 million sentences in English, French, German, Russian, and Chinese .
The ACL OCL Corpus: Advancing Open Science in Computational Linguistics (2023.emnlp-main)

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Challenge: ACL OCL is a scholarly corpus derived from the ACL Anthology . it provides metadata, PDF files, citation graphs and additional structured full texts .
Approach: They present ACL OCL, a scholarly corpus derived from the ACL Anthology . it integrates metadata, PDF files, citation graphs and additional structured full texts . they highlight how it applies to observe trends in computational linguistics .
Outcome: The ACL OCL spans seven decades and contains 73,285 papers . the scholarly corpus is based on the ACL Anthology and is available from HuggingFace .
Two Huge Title and Keyword Generation Corpora of Research Articles (2020.lrec-1)

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Challenge: Recent advances in sequence-to-sequence learning with neural networks have improved the quality of automatically generated text summaries and document keywords.
Approach: They propose to use OAGSX and OAGKX datasets to analyze text summaries and document keywords.
Outcome: The proposed models perform better than previous models on two large datasets . the authors hope to use the results to derive subsets of research articles from more disciplines .
Tracing Syntactic Change in the Scientific Genre: Two Universal Dependency-parsed Diachronic Corpora of Scientific English and German (2022.lrec-1)

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Challenge: a recent study has focused on the syntactic development of scientific discourse in English and German.
Approach: They present two comparable diachronic corpora of scientific English and German from the Late Modern Period (17th c.–19th d.) annotated with Universal Dependencies.
Outcome: The presented corpora are comparable to existing studies on grammatical change in English and German . the results show that the pre-processing steps significantly improve parsing accuracy .

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GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

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