Papers by Sotiris Kotitsas

2 papers
Leveraging fine-tuned Large Language Models with LoRA for Effective Claim, Claimer, and Claim Object Detection (2024.eacl-long)

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Challenge: Existing work on identifying claims has focused on sentence level, neglecting supplementary attributes such as the claimer and claim object of the claim.
Approach: They propose a novel approach to detect claims using large language models in natural language understanding and text generation.
Outcome: The proposed approach transforms claim, claimer and claim object detection task into QA setting.
An Empirical Study on Large-Scale Multi-Label Text Classification Including Few and Zero-Shot Labels (2020.emnlp-main)

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Challenge: Large-scale Multi-label Text Classification (LMTC) is a type of classification that assigns labels to a large set of labels.
Approach: They propose to use probabilistic label trees to improve frequent, few and zero-shot learning . they propose to combine a new state-of-the-art method with pre-trained Transformers .
Outcome: The proposed models outperform existing models on frequent, few and zero-shot learning on three datasets from different domains.

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