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Monte MacDiarmid

Monte MacDiarmid has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Bias, fairness & safety; often with Amanda Askell, Carson Denison, Daniel M. Ziegler.

2 papers in our library · 2023–2024

OpenAlex · h-index 7 · 11 works · 127 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 401 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5134

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

 Affiliations

🎓University of OxfordOxford · United Kingdom2007–2024 · 5 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 workSafety Research · 1 workSocial Sciences · 1 work

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

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Steering Language Models With Activation Engineering (2023 · 233 citations)
    Large language models often have abilities that ordinary prompting or finetuning does not bring out. The authors call this gap an "elicitation overhang". To narrow it, they describe a family of methods called activation engineering, which edits a model's internal activations while it generates text. Their method…
  2. Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training (2024 · 123 citations)
    The paper asks whether an LLM that has learned a hidden, trigger-dependent harmful policy could be cleaned up by today's standard safety training.

All works

4 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. Steering Language Models With Activation EngineeringarXiv:2308.10248Alexander Matt Turner, Lisa Thiergart, Gavin Leech, et al.2023 · 233 citations
  2. Sleeper Agents: Training Deceptive LLMs that Persist Through Safety TrainingarXiv:2401.05566Evan Hubinger, Carson Denison, Jesse Mu, et al.2024 · 123 citations
  3. Alignment faking in large language models ↗arXiv (Cornell University) · no summary yetRyan Greenblatt et al.2024 · 82 citations
  4. Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models ↗arXiv (Cornell University) · no summary yetCarson Denison et al.2024 · 46 citations

 Co-authors here

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

 Cited by

Papers of our library cite their works 401 times (of the 149,439 papers whose bibliographies we read); 108 citing papers with a page here →.

Updated

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