Name
Abstract | ||
|---|---|---|
Next to keeping up with the growing literature in their own and related fields, scholars increasingly also need to rebut pseudo-science and disinformation. To address these challenges, computational work on enhancing search, summarization, and analysis of scholarly documents has flourished. However, the various strands of research on scholarly document processing remain fragmented. To reach to the broader NLP and AI/ML community, pool distributed efforts and enable shared access to published research, we held the 1st Workshop on Scholarly Document Processing at EMNLP 2020 as a virtual event. The SDP workshop consisted of a research track (including a poster session), two invited talks and three Shared Tasks (CL-SciSumm, Lay-Summ and LongSumm), geared towards easier access to scientific methods and results. Website: https://ornlcda.github.io/SDProc |
Year | DOI | Venue |
|---|---|---|
2020 | 10.18653/v1/2020.sdp-1.1 | SDP@EMNLP |
DocType | Volume | Citations |
Conference | 2020.sdp-1 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Muthu Kumar Chandrasekaran | 1 | 35 | 7.24 |
| Guy Feigenblat | 2 | 0 | 1.01 |
| Dayne Freitag | 3 | 2176 | 397.46 |
| Tirthankar Ghosal | 4 | 8 | 8.40 |
| Eduard H. Hovy | 5 | 7450 | 663.27 |
| Philipp Mayr | 6 | 312 | 52.04 |
| Michal Shmueli-Scheuer | 7 | 89 | 16.11 |
| Anita de Waard | 8 | 65 | 13.02 |