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cs.CL2024
Investigating LLMs as Voting Assistants via Contextual Augmentation: A Case Study on the European Parliament Elections 2024
Ilias Chalkidis
In light of the recent 2024 European Parliament elections, we are investigating if LLMs can be used as Voting Advice Applications (VAAs). We audit MISTRAL and MIXTRAL models and ev…
cs.CL2023★ 1 cited
Retrieval-augmented Multi-label Text Classification
Ilias Chalkidis, Yova Kementchedjhieva
Multi-label text classification (MLC) is a challenging task in settings of large label sets, where label support follows a Zipfian distribution. In this paper, we address this prob…
cs.CL2023★ 3 cited
An Exploration of Encoder-Decoder Approaches to Multi-Label Classification for Legal and Biomedical Text
Yova Kementchedjhieva, Ilias Chalkidis
Standard methods for multi-label text classification largely rely on encoder-only pre-trained language models, whereas encoder-decoder models have proven more effective in other cl…