Researchers have developed AutoJourn, a system designed to enhance the responsible creation and evaluation of news generated by large language models (LLMs). The system addresses challenges in automated journalism by extracting diverse perspectives from social media, generating balanced summaries that maintain viewpoint diversity, and identifying and mitigating bias in AI-generated news. AutoJourn integrates advanced prompt engineering and retrieval augmentation techniques, offering users an interface to inspect perspectives, compare summaries, and apply bias-aware rewrites. AI
IMPACT This system could improve the trustworthiness and fairness of AI-generated news content.
RANK_REASON The cluster describes a research paper detailing a new system for automated journalism.
- arXiv
- AutoJourn
- Hugging Face
- large language models
- social media
- Bias Analysis for Uncontrolled Confounding in the Health Sciences.
- prompt engineering
- retrieval augmentation
- Summarisation of the NHG practice guideline 'Anxiety'
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