readme: ---
  license: cc-by-4.0
  ---
  
  
  ## UoM&MMU at TSAR-2022 Shared Task - Prompt Learning for Lexical Simplification: prompt-ls-es-1 
  
  We present **PromptLS**, a method for fine-tuning large pre-trained masked language models to perform the task of Lexical Simplification.
  This model is part of a series of models presented at the [TSAR-2022 Shared Task](https://taln.upf.edu/pages/tsar2022-st/) 
  by the University of Manchester and Manchester Metropolitan University (UoM&MMU) Team in English, Spanish and Portuguese.
  You can find more details about the project in our [GitHub](https://github.com/lmvasque/ls-prompt-tsar2022).
  
  ## Models
  
  Our models were fine-tuned using prompt-learning for **Lexical Simplification**. These are the available models you can use (current model page in bold):
  
  | Model Name                                                           | Run # |  Language   | Setting       |
  |----------------------------------------------------------------------|-------|:-----------:|---------------|
  | [prompt-ls-en-1](https://huggingface.co/lmvasque/prompt-ls-en-1)     | 1     |   English   | fine-tune     |
  | [prompt-ls-en-2](https://huggingface.co/lmvasque/prompt-ls-en-2)     | 2     |   English   | fine-tune     |
  | [roberta-large](https://huggingface.co/roberta-large)                | 3     |   English   | zero-shot    |
  | **[prompt-ls-es-1](https://huggingface.co/lmvasque/prompt-ls-es-1)** | **1** | **Spanish** | **fine-tune** |
  | [prompt-ls-es-2](https://huggingface.co/lmvasque/prompt-ls-es-2)     | 2     |   Spanish   | fine-tune     |
  | [prompt-ls-es-3](https://huggingface.co/lmvasque/prompt-ls-es-3)     | 3     |   Spanish   | fine-tune     |
  | [prompt-ls-pt-1](https://huggingface.co/lmvasque/prompt-ls-pt-1)     | 1     | Portuguese  | fine-tune     |
  | [prompt-ls-pt-2](https://huggingface.co/lmvasque/prompt-ls-pt-2)     | 2     | Portuguese  | fine-tune     |
  | [prompt-ls-pt-3](https://huggingface.co/lmvasque/prompt-ls-pt-3)     | 3     | Portuguese  | fine-tune     |
  
  For the zero-shot setting, we used the original models with no further training. Links to these models are also updated in the table above.
  
  ## Results
  
  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. 
  You can find more details in our [paper](https://drive.google.com/file/d/1x5dRxgcSGAaCCrjsgpCHnYek9G-TmZff/view?usp=share_link).
  
  | Language   | # | Model | Setting      | Prompt1 | Prompt2 | w | k | Acc@1 | A@3 | M@3 | P@3         |
  |------------|---|-------|--------------|---------|---------|---|---|-------|-----|-----|-------------|
  | English    | 1 | RoBERTa-L | fine-tune    | simple | word | 5 | 5 | **0.6353** | **0.5308** | **0.4244** | **0.8739**  |
  | English    | 2 | mBERT | multilingual | easier | word | 10 | 10 | 0.4959 |  0.4235 | 0.3273 | 0.7560 |
  | English    | 3 | RoBERTa-L | zero-shot    | easier | word | 5 | - | 0.2654 | 0.268 | 0.1820 | 0.4906 |
  | Spanish    | 1 | BERTIN | fine-tune    | sinónimo | fácil | - | 3 | 0.3451 | **0.2907** | **0.2238** | **0.5543** |
  | Spanish    | 2 | BERTIN | fine-tune    | palabra | simple | - | 10 | 0.3614 | **0.2907**| 0.2225 | 0.538 |
  | Spanish    | 3 | BERTIN | fine-tune    | sinónimo | fácil | 10 | 10 | **0.3668** | 0.269 |  0.2128 | 0.5326 |
  | Portuguese | 1 | BR_BERTo | fine-tune    | palavra | simples | - | 8 | **0.1711** | 0.1096 | 0.1011 | 0.2486 |
  | Portuguese | 2 | BR_BERTo | fine-tune    | sinônimo | fácil | - | 10 | 0.1363  | 0.0962 | 0.0944 | 0.2379 |
  | Portuguese | 3 | BR_BERTo | fine-tune    | sinônimo | simples | 5 | 10 | 0.1577 | **0.1283**| **0.1071**| **0.2834**|
  
  
  ## Citation
  
  If you use our results and scripts in your research, please cite our work: 
  "[UoM&MMU at TSAR-2022 Shared Task: Prompt Learning for Lexical Simplification](https://drive.google.com/file/d/1x5dRxgcSGAaCCrjsgpCHnYek9G-TmZff/view?usp=share_link)". 
  
  ```
  @inproceedings{vasquez-rodriguez-etal-2022-prompt-ls,
      title = "UoM\&MMU at TSAR-2022 Shared Task: Prompt Learning for Lexical Simplification",
      author = "V{\'a}squez-Rodr{\'\i}guez, Laura  and
        Nguyen, Nhung T. H. and
        Shardlow, Matthew and
        Ananiadou, Sophia",
      booktitle = "Shared Task on Text Simplification, Accessibility, and Readability (TSAR-2022), EMNLP 2022",
      month = dec,
      year = "2022",
  }
  ```
  