Elias Zavitsanos


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DICE @ ML-ESG-3: ESG Impact Level and Duration Inference Using LLMs for Augmentation and Contrastive Learning
Konstantinos Bougiatiotis | Andreas Sideras | Elias Zavitsanos | Georgios Paliouras
Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing @ LREC-COLING 2024

We present the submission of team DICE for ML-ESG-3, the 3rd Shared Task on Multilingual ESG impact duration inference in the context of the joint FinNLP-KDF workshop series. The task provides news articles and seeks to determine the impact and duration of an event in the news article may have on a company. We experiment with various baselines and discuss the results of our best-performing submissions based on contrastive pre-training and a stacked model based on the bag-of-words assumption and sentence embeddings. We also explored the label correlations among events stemming from the same news article and the correlations between impact level and impact length. Our analysis shows that even simple classifiers trained in this task can achieve comparable performance with more complex models, under certain conditions.


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DICoE@FinSim-3: Financial Hypernym Detection using Augmented Terms and Distance-based Features
Lefteris Loukas | Konstantinos Bougiatiotis | Manos Fergadiotis | Dimitris Mavroeidis | Elias Zavitsanos
Proceedings of the Third Workshop on Financial Technology and Natural Language Processing