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Miles Turpin

Miles Turpin has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Reasoning, Bias, fairness & safety; often with Abulhair Saparov, Daniel Paleka, Ekdeep Singh Lubana.

2 papers in our library · 2023–2024

OpenAlex · h-index 2 · 6 works · 223 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 444 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #3534

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 workEngineering · 1 workSafety Research · 1 workSafety, Risk, Reliability and Quality · 1 workSocial Sciences · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 1 workBias, fairness & safety · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Few-shot learning · 1 work

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting (2023 · 586 citations)
    The paper asks whether the step-by-step reasoning that LLMs write in chain-of-thought (CoT) prompting reflects the real reason behind their answers.
  2. Foundational Challenges in Assuring Alignment and Safety of Large Language Models (2024 · 87 citations)
    This agenda-style paper by Anwar and a large multi-institution team asks what still prevents large language models from being reliably aligned and safe.

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought PromptingConference on Neural Information Processing Systems (NeurIPS)Miles Turpin, Julian Michael, Ethan Perez, et al.2023 · 586 citations
  2. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  3. Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-Thought ↗arXiv (Cornell University) · no summary yetJames Chua et al.2024 · 10 citations

 Co-authors here

9 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 444 times (of the 149,439 papers whose bibliographies we read); 111 citing papers with a page here →.

Updated

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