Update README.md

README.md

@@ -1,5 +1,5 @@
 ---
-license: cc-by-4.0
+license: mit
 language:
 - pt
 - vmw
@@ -11,6 +11,9 @@ task_categories:
 # Detecting Loanwords in Emakhuwa
 Paper: Detecting Loanwords in Emakhuwa: An Extremely Low-Resource {B}antu Language Exhibiting Significant Borrowing from {P}ortuguese
 ´´´´
+
+```bibtex
+
 @inproceedings{ali-etal-2024-detecting,
     title = "Detecting Loanwords in Emakhuwa: An Extremely Low-Resource {B}antu Language Exhibiting Significant Borrowing from {P}ortuguese",
     author = "Ali, Felermino Dario Mario  and
@@ -31,14 +34,10 @@ Paper: Detecting Loanwords in Emakhuwa: An Extremely Low-Resource {B}antu Langua
     pages = "4750--4759",
     abstract = "The accurate identification of loanwords within a given text holds significant potential as a valuable tool for addressing data augmentation and mitigating data sparsity issues. Such identification can improve the performance of various natural language processing tasks, particularly in the context of low-resource languages that lack standardized spelling conventions.This research proposes a supervised method to identify loanwords in Emakhuwa, borrowed from Portuguese. Our methodology encompasses a two-fold approach. Firstly, we employ traditional machine learning algorithms incorporating handcrafted features, including language-specific and similarity-based features. We build upon prior studies to extract similarity features and propose utilizing two external resources: a Sequence-to-Sequence model and a dictionary. This innovative approach allows us to identify loanwords solely by analyzing the target word without prior knowledge about its donor counterpart. Furthermore, we fine-tune the pre-trained CANINE model for the downstream task of loanword detection, which culminates in the impressive achievement of the F1-score of 93{\%}. To the best of our knowledge, this study is the first of its kind focusing on Emakhuwa, and the preliminary results are promising as they pave the way to further advancements.",
 }
-´´´
 
 # Licence
 This project is released under the MIT license.
 
-# Acknowledgements
-The base code is based on a [previous](https://github.com/csu-signal/loan-word-detection) implementation.
-
 # Contact
 [Felermino Ali](https://felerminoali.github.io/)