@inproceedings{ghosh-naskar-2022-lipi-finnlp,
title = "{LIPI} at the {F}in{NLP}-2022 {ERAI} Task: Ensembling Sentence Transformers for Assessing Maximum Possible Profit and Loss from Online Financial Posts",
author = "Ghosh, Sohom and
Naskar, Sudip Kumar",
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://aclanthology.org/2022.finnlp-1.13",
doi = "10.18653/v1/2022.finnlp-1.13",
pages = "111--115",
abstract = "Using insights from social media for making investment decisions has become mainstream. However, in the current era of information ex- plosion, it is essential to mine high-quality so- cial media posts. The FinNLP-2022 ERAI task deals with assessing Maximum Possible Profit (MPP) and Maximum Loss (ML) from social me- dia posts relating to finance. In this paper, we present our team LIPI{'}s approach. We ensem- bled a range of Sentence Transformers to quan- tify these posts. Unlike other teams with vary- ing performances across different metrics, our system performs consistently well. Our code is available here \url{https://github.com/sohomghosh/LIPI_ERAI_} FinNLP{\_}EMNLP- 2022/",
}
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<abstract>Using insights from social media for making investment decisions has become mainstream. However, in the current era of information ex- plosion, it is essential to mine high-quality so- cial media posts. The FinNLP-2022 ERAI task deals with assessing Maximum Possible Profit (MPP) and Maximum Loss (ML) from social me- dia posts relating to finance. In this paper, we present our team LIPI’s approach. We ensem- bled a range of Sentence Transformers to quan- tify these posts. Unlike other teams with vary- ing performances across different metrics, our system performs consistently well. Our code is available here https://github.com/sohomghosh/LIPI_ERAI_ FinNLP_EMNLP- 2022/</abstract>
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%0 Conference Proceedings
%T LIPI at the FinNLP-2022 ERAI Task: Ensembling Sentence Transformers for Assessing Maximum Possible Profit and Loss from Online Financial Posts
%A Ghosh, Sohom
%A Naskar, Sudip Kumar
%Y Chen, Chung-Chi
%Y Huang, Hen-Hsen
%Y Takamura, Hiroya
%Y Chen, Hsin-Hsi
%S Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F ghosh-naskar-2022-lipi-finnlp
%X Using insights from social media for making investment decisions has become mainstream. However, in the current era of information ex- plosion, it is essential to mine high-quality so- cial media posts. The FinNLP-2022 ERAI task deals with assessing Maximum Possible Profit (MPP) and Maximum Loss (ML) from social me- dia posts relating to finance. In this paper, we present our team LIPI’s approach. We ensem- bled a range of Sentence Transformers to quan- tify these posts. Unlike other teams with vary- ing performances across different metrics, our system performs consistently well. Our code is available here https://github.com/sohomghosh/LIPI_ERAI_ FinNLP_EMNLP- 2022/
%R 10.18653/v1/2022.finnlp-1.13
%U https://aclanthology.org/2022.finnlp-1.13
%U https://doi.org/10.18653/v1/2022.finnlp-1.13
%P 111-115
Markdown (Informal)
[LIPI at the FinNLP-2022 ERAI Task: Ensembling Sentence Transformers for Assessing Maximum Possible Profit and Loss from Online Financial Posts](https://aclanthology.org/2022.finnlp-1.13) (Ghosh & Naskar, FinNLP 2022)
ACL