Papers by Toyin D. Aguda
Large Language Models as Financial Data Annotators: A Study on Effectiveness and Efficiency (2024.lrec-main)
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Toyin D. Aguda, Suchetha Siddagangappa, Elena Kochkina, Simerjot Kaur, Dongsheng Wang, Charese Smiley
| Challenge: | Large Language Models (LLMs) have demonstrated remarkable performance in data annotation tasks on general domain datasets, but their effectiveness on domain specific datasets remains under-explored. |
| Approach: | They compare the annotations produced by three LLMs against expert annotators and crowdworkers. |
| Outcome: | The proposed models outperform expert crowdworkers and crowd-sourced annotators on domain specific datasets. |