Name
Abstract | ||
|---|---|---|
This paper introduces a novel orchestration framework, called CFO (COMPUTATION FLOW ORCHESTRATOR), for building, experimenting with, and deploying interactive NLP (Natural Language Processing) and IR (Information Retrieval) systems to production environments. We then demonstrate a question answering system built using this framework which incorporates state-of-the-art BERT based MRC (Machine Reading Comprehension) with IR components to enable end-to-end answer retrieval. Results from the demo system are shown to be high quality in both academic and industry domain specific settings. Finally, we discuss best practices when (pre-)training BERT based MRC models for production systems. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.18653/v1/D19-3006 | EMNLP/IJCNLP (3) |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 11 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rishav Chakravarti | 1 | 0 | 1.69 |
| Cezar Pendus | 2 | 0 | 0.34 |
| Andrzej Sakrajda | 3 | 0 | 0.34 |
| Anthony Ferritto | 4 | 0 | 1.69 |
| Lin Pan | 5 | 0 | 2.03 |
| Michael Glass | 6 | 0 | 0.34 |
| Vittorio Castelli | 7 | 928 | 129.71 |
| J. W. Murdock | 8 | 162 | 12.22 |
| Radu Florian | 9 | 924 | 91.44 |
| Salim Roukos | 10 | 6248 | 845.50 |
| Avi Sil | 11 | 1 | 1.83 |