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Lujain Ibrahim

Lujain Ibrahim has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining; often with Myra Cheng, Cinoo Lee, Dan Jurafsky.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 7 · 29 works · 216 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 49 times in our library · 7 more in our library without a page yet · ⭐ Paper Stars ranking: #5726

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 Kingdom2024–2026 · 15 paperscurrent🏢Google DeepMindLondon · United Kingdom2026 · 1 papercurrent🎓New York University Abu DhabiAbu Dhabi · United Arab Emirates2020–2023 · 3 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 9The field of science this work belongs to (OpenAlex fields).Social Sciences · 2 worksPsychology · 1 workSafety Research · 2 worksSocial Psychology · 1 workSociology and Political Science · 1 workArtificial Intelligence · 1 workArts and Humanities · 1 workComputer Science · 1 workLanguage and Linguistics · 1 work

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

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. ELEPHANT: Measuring and understanding social sycophancy in LLMs (2025 · 188 citations)
    Earlier sycophancy research checks whether an LLM drops a factual answer to agree with a belief the user states outright.
  2. Thinking beyond the anthropomorphic paradigm benefits LLM research (2026 · 8 citations)
    This position paper examines how the habit of describing LLMs in human terms shapes NLP research, and argues that the field relies on it too heavily.

All works

9 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. ELEPHANT: Measuring and understanding social sycophancy in LLMsScienceMyra Cheng, Sunny Yu, Cinoo Lee, et al.2025 · 188 citations
  2. Thinking beyond the anthropomorphic paradigm benefits LLM researchAnnual Meeting of the Association for Computational Linguistics (ACL)Lujain Ibrahim, Myra Cheng2026 · 8 citations
  3. Measuring and Mitigating (Over)reliance to Build Human-Compatible AI ↗Proceedings of the AAAI/ACM Conference on AI Ethics and Society · no summary yetLujain Ibrahim et al.2026 · 7 citations
  4. Sycophantic AI makes human interaction feel more effortful and less satisfying over time ↗arXiv (Cornell University) · no summary yetLujain Ibrahim et al.2026 · 6 citations
  5. Verbalizing LLMs' assumptions to explain and control sycophancy ↗arXiv (Cornell University) · no summary yetMyra Cheng et al.2026 · 2 citations
  6. Verbalizing LLMs' Assumptions About the User to Calibrate Expectations and Reduce Sycophancy ↗Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA) · no summary yetMyra Cheng et al.2026 · 1 citation
  7. Offloading Score: Measuring AI Reliance Through Counterfactual Workflows ↗arXiv (Cornell University) · no summary yetVishakh Padmakumar et al.2026 · 1 citation
  8. LLMs as Oracles: Reliance on LLMs for Subjective Personal Questions ↗arXiv (Cornell University) · no summary yetMyra Cheng et al.2026
  9. Warning labels shift perceptions of sycophantic AI, but not its influence ↗arXiv (Cornell University) · no summary yetLujain Ibrahim et al.2026

 Co-authors here

4 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 49 times (of the 149,439 papers whose bibliographies we read); 15 citing papers with a page here →.

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