Influences on LLM Calibration: A Study of Response Agreement, Loss Functions, and Prompt Styles (2025 · 11 citations)
LLMs often express confidence that does not match how often they are actually right. Earlier calibration methods were usually tested on only a few models and prompt formats. This paper runs a controlled comparison across 12 LLMs from five model families (2B–72B parameters), four prompt styles (Verbalized, Zero-shot…
Explaining Generalization of AI-Generated Text Detectors Through Linguistic Analysis (2026 · 2 citations)
Fine-tuned classifiers that flag machine-written text score almost perfectly on data resembling their training material. Their accuracy falls, however, when the prompt, the generating model, or the domain changes. Earlier studies documented these drops but rarely explained them.

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Updated 31 October 2026