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Raphael Milliere

Raphael Milliere has 3 papers in our library, in 2023–2026, most of them on Language models & pretraining, Evaluation & benchmarks.

3 papers in our library · 2023–2026

OpenAlex · ORCID · Wikidata · h-index 12 · 55 works · 1,755 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 1,263 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #7827

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 Kingdom2017–2026 · 16 papersEducationEmployment · Jesus College; Philosophycurrent🎓Macquarie UniversitySydney · Australia2023–2025 · 7 papersEmployment🎓Columbia UniversityNew York · United States2020–2023 · 7 papersEmployment 2020–2023 · Presidential Scholar in Society and Neuroscience, Center for Science and Society

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 10The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksPsychology · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksHistory and Philosophy of Science · 2 worksDevelopmental and Educational Psychology · 1 workCognitive Neuroscience · 1 workExperimental and Cognitive Psychology · 1 workNeuroscience · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksEvaluation & benchmarks · 1 work

 Works by year

2020s

20261 paper20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Language Models as Models of Language (2024 · 21 citations)
    This chapter is a review and position piece, not an empirical study. It asks whether neural language models belong in theoretical linguistics as accounts of how humans acquire and represent grammar, or whether they are only engineering tools. The paper releases no corpus, treebank or model and surveys existing…
  2. The Vector Grounding Problem (2023 · 20 citations)
    Harnad's 1990 Symbol Grounding Problem asked whether symbols in an AI system can mean anything beyond what human readers attribute to them.
  3. Anthropocentric Bias in Language Model Evaluation (2026 · 8 citations)
    Debates about what large language models (LLMs) can cognitively do usually guard against anthropomorphism but neglect the opposite error: judging LLMs by human standards without justification.

All works

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

  1. Language Models as Models of LanguagearXiv:2408.07144Raphael Milliere2024 · 21 citations
  2. The Vector Grounding ProblemarXiv:2304.01481Dimitri Coelho Mollo, Raphael Milliere2023 · 20 citations
  3. LLMs as models for analogical reasoning ↗Journal of Memory and Language · no summary yetSam Musker et al.2025 · 18 citations
  4. Normative Conflicts and Shallow AI Alignment ↗arXiv:2506.04679 · Milliere, R. (2025). Normative conflicts and shallow AI alignment. Philosophical Studies, 1-44 · no summary yetRaphael Milliere2025 · 11 citations
  5. Anthropocentric Bias in Language Model EvaluationComputational LinguisticsRaphaël Millière, Charles Rathkopf2026 · 8 citations
  6. Learning Groundings In-context with LLMs ↗no summary yetSamuel Musker et al.2023

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 1,263 times (of the 149,439 papers whose bibliographies we read); 310 citing papers with a page here →.

Updated

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