57 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Brno University of TechnologyCZ13 papers
- Slovak University of Technology in BratislavaSK6 papers
- Adobe Systems (United States)US3 papers
- Comenius University BratislavaSK3 papers
- Amazon (Germany)DE2 papers
- University of SheffieldGB2 papers
- Agence France-PresseFR1 paper
- Amazon (United Kingdom)GB1 paper
- Amazon (United States)US1 paper
- Amsterdam University of the ArtsNL1 paper
- Central European UniversityAT1 paper
- Fondazione Bruno KesslerIT1 paper
Showing 2023 · cs.CLShow all
2 papers · 2 filters
cs.CL2023★ 23 cited
Comparison between parameter-efficient techniques and full fine-tuning: A case study on multilingual news article classification
Olesya Razuvayevskaya, Ben Wu, Joao A. Leite +5
Adapters and Low-Rank Adaptation (LoRA) are parameter-efficient fine-tuning techniques designed to make the training of language models more efficient. Previous results demonstrate…
cs.CL2023★ 5 cited
KInITVeraAI at SemEval-2023 Task 3: Simple yet Powerful Multilingual Fine-Tuning for Persuasion Techniques Detection
Timo Hromadka, Timotej Smolen, Tomas Remis +2
This paper presents the best-performing solution to the SemEval 2023 Task 3 on the subtask 3 dedicated to persuasion techniques detection. Due to a high multilingual character of t…