laura.vasquezrodriguez
commited on
Commit
•
f7fa1d6
1
Parent(s):
a1bc52e
Update paper link in README.md
Browse files
README.md
CHANGED
@@ -3,7 +3,7 @@ license: cc-by-4.0
|
|
3 |
---
|
4 |
|
5 |
|
6 |
-
##
|
7 |
|
8 |
We present **PromptLS**, a method for fine-tuning large pre-trained masked language models to perform the task of Lexical Simplification.
|
9 |
This model is part of a series of models presented at the [TSAR-2022 Shared Task](https://taln.upf.edu/pages/tsar2022-st/)
|
@@ -31,7 +31,7 @@ For the zero-shot setting, we used the original models with no further training.
|
|
31 |
## Results
|
32 |
|
33 |
We include the [official results](https://github.com/LaSTUS-TALN-UPF/TSAR-2022-Shared-Task/tree/main/results/official) from the competition test set as a reference. However, we encourage the users to also check our results in the development set, which show an increased performance for Spanish and Portuguese.
|
34 |
-
You can find more details in our [paper](https://drive.google.com/file/d/
|
35 |
|
36 |
| Language | # | Model | Setting | Prompt1 | Prompt2 | w | k | Acc@1 | A@3 | M@3 | P@3 |
|
37 |
|------------|---|-------|--------------|---------|---------|---|---|-------|-----|-----|-------------|
|
@@ -49,11 +49,11 @@ You can find more details in our [paper](https://drive.google.com/file/d/10nOMKu
|
|
49 |
## Citation
|
50 |
|
51 |
If you use our results and scripts in your research, please cite our work:
|
52 |
-
"[UoM&MMU at TSAR-2022 Shared Task
|
53 |
|
54 |
```
|
55 |
@inproceedings{vasquez-rodriguez-etal-2022-prompt-ls,
|
56 |
-
title = "UoM\&MMU at TSAR-2022 Shared Task
|
57 |
author = "V{\'a}squez-Rodr{\'\i}guez, Laura and
|
58 |
Nguyen, Nhung T. H. and
|
59 |
Shardlow, Matthew and
|
@@ -62,4 +62,4 @@ If you use our results and scripts in your research, please cite our work:
|
|
62 |
month = dec,
|
63 |
year = "2022",
|
64 |
}
|
65 |
-
```
|
|
|
3 |
---
|
4 |
|
5 |
|
6 |
+
## UoM&MMU at TSAR-2022 Shared Task - Prompt Learning for Lexical Simplification: prompt-ls-pt-1
|
7 |
|
8 |
We present **PromptLS**, a method for fine-tuning large pre-trained masked language models to perform the task of Lexical Simplification.
|
9 |
This model is part of a series of models presented at the [TSAR-2022 Shared Task](https://taln.upf.edu/pages/tsar2022-st/)
|
|
|
31 |
## Results
|
32 |
|
33 |
We include the [official results](https://github.com/LaSTUS-TALN-UPF/TSAR-2022-Shared-Task/tree/main/results/official) from the competition test set as a reference. However, we encourage the users to also check our results in the development set, which show an increased performance for Spanish and Portuguese.
|
34 |
+
You can find more details in our [paper](https://drive.google.com/file/d/1x5dRxgcSGAaCCrjsgpCHnYek9G-TmZff/view?usp=share_link).
|
35 |
|
36 |
| Language | # | Model | Setting | Prompt1 | Prompt2 | w | k | Acc@1 | A@3 | M@3 | P@3 |
|
37 |
|------------|---|-------|--------------|---------|---------|---|---|-------|-----|-----|-------------|
|
|
|
49 |
## Citation
|
50 |
|
51 |
If you use our results and scripts in your research, please cite our work:
|
52 |
+
"[UoM&MMU at TSAR-2022 Shared Task: Prompt Learning for Lexical Simplification](https://drive.google.com/file/d/1x5dRxgcSGAaCCrjsgpCHnYek9G-TmZff/view?usp=share_link)".
|
53 |
|
54 |
```
|
55 |
@inproceedings{vasquez-rodriguez-etal-2022-prompt-ls,
|
56 |
+
title = "UoM\&MMU at TSAR-2022 Shared Task: Prompt Learning for Lexical Simplification",
|
57 |
author = "V{\'a}squez-Rodr{\'\i}guez, Laura and
|
58 |
Nguyen, Nhung T. H. and
|
59 |
Shardlow, Matthew and
|
|
|
62 |
month = dec,
|
63 |
year = "2022",
|
64 |
}
|
65 |
+
```
|