@inproceedings{goel-bommidi-2022-semeval,
    title = "Wolfies at {S}em{E}val-2022 Task 8: Feature extraction pipeline with transformers for Multi-lingual news article similarity",
    author = "Goel, Nikhil  and
      Bommidi, Ranjith Reddy",
    editor = "Emerson, Guy  and
      Schluter, Natalie  and
      Stanovsky, Gabriel  and
      Kumar, Ritesh  and
      Palmer, Alexis  and
      Schneider, Nathan  and
      Singh, Siddharth  and
      Ratan, Shyam",
    booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2022.semeval-1.159/",
    doi = "10.18653/v1/2022.semeval-1.159",
    pages = "1129--1135",
    abstract = "This work is about finding the similarity between a pair of news articles. There are seven different objective similarity metrics provided in the dataset for each pair and the news articles are in multiple different languages. On top of the pre-trained embedding model, we calculated cosine similarity for baseline results and feed-forward neural network was then trained on top of it to improve the results. We also built separate pipelines for each similarity metric for feature extraction. We could see significant improvement from baseline results using feature extraction and feed-forward neural network."
}