ParsiNLU: A Suite of Language Understanding Challenges for Persian

Autor: Daniel Khashabi, Arman Cohan, Siamak Shakeri, Pedram Hosseini, Pouya Pezeshkpour, Malihe Alikhani, Moin Aminnaseri, Marzieh Bitaab, Faeze Brahman, Sarik Ghazarian, Mozhdeh Gheini, Arman Kabiri, Rabeeh Karimi Mahabagdi, Omid Memarrast, Ahmadreza Mosallanezhad, Erfan Noury, Shahab Raji, Mohammad Sadegh Rasooli, Sepideh Sadeghi, Erfan Sadeqi Azer, Niloofar Safi Samghabadi, Mahsa Shafaei, Saber Sheybani, Ali Tazarv, Yadollah Yaghoobzadeh

Publikováno v: Transactions of the Association for Computational Linguistics, Vol 9, Pp 1147-1162 (2021)

AbstractDespite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English. This work focuses on Persian language,

Externí odkaz: https://doaj.org/article/628c3c423b8e4fc681edcc882bbb9c33

ParsiNLU: A Suite of Language Understanding Challenges for Persian

Autor: Saber Sheybani, Sarik Ghazarian, Shahab Raji, Erfan Noury, Arman Kabiri, Yadollah Yaghoobzadeh, Niloofar Safi Samghabadi, Moin Aminnaseri, Erfan Sadeqi Azer, Faeze Brahman, Siamak Shakeri, Daniel Khashabi, Ali Tazarv, Mozhdeh Gheini, Omid Memarrast, Mohammad Sadegh Rasooli, Mahsa Shafaei, Malihe Alikhani, Marzieh Bitaab, Pouya Pezeshkpour, Arman Cohan, Sepideh Sadeghi, Rabeeh Karimi Mahabagdi, Pedram Hosseini, Ahmadreza Mosallanezhad

Publikováno v: Transactions of the Association for Computational Linguistics. 9:1147-1162

Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English. This work focuses on Persian language, one of t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b9b56afd3f51a87f151b56eb4f92e810
https://doi.org/10.1162/tacl_a_00419

Generating Scientific Claims for Zero-Shot Scientific Fact Checking

Autor: Dustin Wright, David Wadden, Kyle Lo, Bailey Kuehl, Arman Cohan, Isabelle Augenstein, Lucy Wang

Publikováno v: Wright, D, Wadden, D, Lo, K, Kuehl, B, Cohan, A, Augenstein, I & Wang, L L 2022, Generating Scientific Claims for Zero-Shot Scientific Fact Checking . in Generating Scientific Claims for Zero-Shot Scientific Fact Checking . Association for Computational Linguistics, 60th Annual Meeting of the Association for Computational Linguistics, Dublin, Ireland, 23/05/2022 . https://doi.org/10.18653/v1/2022.acl-long.175

Automated scientific fact checking is difficult due to the complexity of scientific language and a lack of significant amounts of training data, as annotation requires domain expertise. To address this challenge, we propose scientific claim generatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::207da191730e76de06a43f07444f95b8
https://doi.org/10.18653/v1/2022.acl-long.175

MultiVerS: Improving scientific claim verification with weak supervision and full-document context

Autor: David Wadden, Kyle Lo, Lucy Wang, Arman Cohan, Iz Beltagy, Hannaneh Hajishirzi

The scientific claim verification task requires an NLP system to label scientific documents which Support or Refute an input claim, and to select evidentiary sentences (or rationales) justifying each predicted label. In this work, we present MultiVer

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96927cf72bd07e364dc7d5ef98fb9e0d
http://arxiv.org/abs/2112.01640

Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity

Autor: Sheshera Mysore, Arman Cohan, Tom Hope

We present a new scientific document similarity model based on matching fine-grained aspects of texts. To train our model, we exploit a naturally-occurring source of supervision: sentences in the full-text of papers that cite multiple papers together

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a3c225024c39fd171f2b4ba8873cd68