@inproceedings{kang-el-maarouf-2022-finsim4,
    title = "{F}in{S}im4-{ESG} Shared Task: Learning Semantic Similarities for the Financial Domain. Extended edition to {ESG} insights",
    author = "Kang, Juyeon  and
      El Maarouf, Ismail",
    editor = "Chen, Chung-Chi  and
      Huang, Hen-Hsen  and
      Takamura, Hiroya  and
      Chen, Hsin-Hsi",
    booktitle = "Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.finnlp-1.28/",
    doi = "10.18653/v1/2022.finnlp-1.28",
    pages = "211--217",
    abstract = "This paper describes FinSim4-ESG 1 shared task organized in the 4th FinNLP workshopwhich is held in conjunction with the IJCAI-ECAI-2022 confer- enceThis year, the FinSim4 is extended to the Environment, Social and Government (ESG) insights and proposes two subtasks, one for ESG Taxonomy Enrichment and the other for Sustainable Sentence Prediction. Among the 28 teams registered to the shared task, a total of 8 teams submitted their systems results and 6 teams also submitted a paper to describe their method. The winner of each subtask shows good performance results of 0.85{\%} and 0.95{\%} in terms of accuracy, respectively."
}