TY - GEN
T1 - Can a Transformer Assist in Scientific Writing? Generating Semantic Web Paper Snippets with GPT-2
AU - Meroño-Peñuela, Albert
AU - Spagnuelo, Dayana
AU - GPT-2
PY - 2020
Y1 - 2020
N2 - The Semantic Web community has produced a large body of literature that is becoming increasingly difficult to manage, browse, and use. Recent work on attention-based, sequence-to-sequence Transformer neural architecture has produced language models that generate surprisingly convincing synthetic conditional text samples. In this demonstration, we re-train the GPT-2 architecture using the complete corpus of proceedings of the International Semantic Web Conference since 2002 until 2019. We use user-provided sentences to conditionally sample paper snippets, therefore illustrating cases where this model can help at addressing challenges in scientific paper writing, such as navigating extensive literature, explaining the Semantic Web core concepts, providing definitions, and even inspiring new research ideas.
AB - The Semantic Web community has produced a large body of literature that is becoming increasingly difficult to manage, browse, and use. Recent work on attention-based, sequence-to-sequence Transformer neural architecture has produced language models that generate surprisingly convincing synthetic conditional text samples. In this demonstration, we re-train the GPT-2 architecture using the complete corpus of proceedings of the International Semantic Web Conference since 2002 until 2019. We use user-provided sentences to conditionally sample paper snippets, therefore illustrating cases where this model can help at addressing challenges in scientific paper writing, such as navigating extensive literature, explaining the Semantic Web core concepts, providing definitions, and even inspiring new research ideas.
KW - Natural language generation
KW - Scholarly communication
KW - Semantic Web papers
UR - http://www.scopus.com/inward/record.url?scp=85097303310&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097303310&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-62327-2_27
DO - 10.1007/978-3-030-62327-2_27
M3 - Conference contribution
AN - SCOPUS:85097303310
SN - 9783030623265
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 158
EP - 163
BT - The Semantic Web
A2 - Harth, Andreas
A2 - Presutti, Valentina
A2 - Troncy, Raphaël
A2 - Acosta, Maribel
A2 - Polleres, Axel
A2 - Fernández, Javier D.
A2 - Xavier Parreira, Josiane
A2 - Hartig, Olaf
A2 - Hose, Katja
A2 - Cochez, Michael
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th Extended Semantic Web Conference, ESWC 2020
Y2 - 31 May 2020 through 4 June 2020
ER -
