add readme
Browse files
README.md
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
language: "`en`"
|
| 3 |
+
thumbnail: "https://camo.githubusercontent.com/7d080b7a769f7fdf64ac0ebeb47b039cb50be35287e3071f9d633f0fe33e7596/68747470733a2f2f692e6962622e636f2f33544331576d472f737065637465722d6c6f676f2d63726f707065642e706e67"
|
| 4 |
+
license: "apache 2.0"
|
| 5 |
+
datasets:
|
| 6 |
+
- SciDocs
|
| 7 |
+
metrics:
|
| 8 |
+
- F1
|
| 9 |
+
- accuracy
|
| 10 |
+
- map
|
| 11 |
+
- ndcg
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
## SPECTER
|
| 15 |
+
|
| 16 |
+
SPECTER is a pre-trained language model to generate document-level embedding of documents. It is pre-trained on a a powerful signal of document-level relatedness: the citation graph. Unlike existing pretrained language models, SPECTER can be easily applied to downstream applications without task-specific fine-tuning.
|
| 17 |
+
|
| 18 |
+
Paper: [SPECTER: Document-level Representation Learning using Citation-informed Transformers](https://arxiv.org/pdf/2004.07180.pdf)
|
| 19 |
+
|
| 20 |
+
Original Repo: [Github](https://github.com/allenai/specter)
|
| 21 |
+
|
| 22 |
+
Evaluation Benchmark: [SciDocs](https://github.com/allenai/scidocs)
|
| 23 |
+
|
| 24 |
+
Authors: *Arman Cohan, Sergey Feldman, Iz Beltagy, Doug Downey, Daniel S. Weld*
|
| 25 |
+
|