A new study published on arXiv explores how the process of data annotation can improve the competence of human annotators, particularly those with expertise. The research involved 25 annotators across five groups who identified 20 social influence techniques in over a thousand dialogues. Results showed a significant increase in annotators' self-perceived competence and confidence, with experts demonstrating a more pronounced effect. This enhanced annotator skill also positively impacted the performance of Large Language Models trained on the annotated data. AI
IMPACT Suggests that improved human annotation quality can lead to better LLM performance.
RANK_REASON The cluster contains a research paper published on arXiv detailing a study on data annotation. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- arXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- Hugging Face
- Influence Flower
- Maciej Markiewicz
- ScienceCast
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