---
title: "Scott A. Hale — papers of 2023 — 3 papers, the most cited first"
description: "Scott A. Hale — papers of 2023: 3 papers on Elamur Research, the most cited first — what each work is about in our own words."
canonical: "https://research.elamur.ai/free/en/authors/scott-a-hale/year/2023/"
---
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# Scott A. Hale — papers of 2023 — 3 papers, the most cited first

3 papers · [all years of Scott A. Hale](https://md.research.elamur.ai/free/en/authors/scott-a-hale/#years)

**[Factuality Challenges in the Era of Large Language Models](https://md.research.elamur.ai/free/en/papers/augenstein-2023-factuality-challenges-era-large-language/) [Nature Machine Intelligence](https://md.research.elamur.ai/free/en/venues/nature-machine-intelligence/)**Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, et al.*2023 · 243 citations*

- [Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback arXiv:2303.05453](https://md.research.elamur.ai/free/en/papers/kirk-2023-personalisation-within-bounds-risk-taxonomy/) — Hannah Rose Kirk, Bertie Vidgen, Paul Rottger, et al. · 2023 · 57 citations
- [SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models arXiv:2311.08370](https://md.research.elamur.ai/free/en/papers/vidgen-2023-simplesafetytests-test-suite-identifying-critical/) — Bertie Vidgen, Nino Scherrer, Hannah Rose Kirk, et al. · 2023 · 42 citations