A new research paper identifies a rhetorical figure called epanorthosis, or self-correction, which large language models systematically overuse. The study posits this overuse stems from training data rich in promotional content and reinforcement learning techniques that favor emphatic phrasing. Researchers propose an 'Epanorthosis Index' to measure this tendency and explore mitigation strategies, including lightweight adapters and instruction tuning, aiming to calibrate model output to human rhetorical styles across different genres. AI
IMPACT Identifies a specific linguistic tendency in LLMs and proposes methods for calibration, potentially improving model output quality and naturalness.
RANK_REASON Research paper published on arXiv detailing a specific linguistic phenomenon in LLMs.
Read on Hugging Face Daily Papers →
- Cicero
- epanorthosis
- Fontanier
- large language models
- LoRA
- Quintilian
- reinforcement learning from human feedback
- epanorthis
- Epanorthosis Index
- Hugging Face
- LoRA adapters
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