"The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case ..."

Tomás Horych et al. (2025)

> Home

Details and statistics

DOI: 10.18653/V1/2025.FINDINGS-NAACL.75

access: open

type: Conference or Workshop Paper

metadata version: 2025-06-13

- view
  - electronic edition via DOI (open access)
  - electronic edition @ aclanthology.org (open access)
  authority control:
- export record
  dblp key:
  - conf/naacl/HorychMRGGAS25
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/naacl/HorychMRGGAS25
Tomás Horych, Christoph Mandl, Terry Ruas, André Greiner-Petter, Bela Gipp, Akiko Aizawa, Timo Spinde:
The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection. NAACL (Findings) 2025: 1370-1386

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.