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Author

Lujain Ibrahim

Observed name: Ibrahim, Lujain
ORCID: 0000-0002-0395-784X
Observed ORCID: 0000-0002-0395-784X
OpenAlex ID: A5088109643
Explainable Prediction of Acute Myocardial Infarction Using Machine Learning and Shapley Values
2020 · Lujain Ibrahim, Munib Mesinovic, et al. · IEEE Access · 123
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Training language models to be warm can reduce accuracy and increase sycophancy
2026 · Lujain Ibrahim, Franziska Sofia Hafner, et al. · Nature · 26
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Comparing the persuasiveness of role-playing large language models and human experts on polarized U.S. political issues
2025 · Kobi Hackenburg, Lujain Ibrahim, et al. · AI & Society · 25
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Measuring what Matters: Construct Validity in Large Language Model Benchmarks
2025 · Andrew M. Bean, Ryan Othniel Kearns, et al. · neural information processing systems · 12
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Towards Interactive Evaluations for Interaction Harms in Human-AI Systems
2025 · Lujain Ibrahim, Saffron Huang, et al. · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · 11
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Open Problems in Technical AI Governance
2024 · Reuel, Anka, Bucknall, Ben, et al. · arXiv (Cornell University) · 9
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Multi-turn Evaluation of Anthropomorphic Behaviours in Large Language Models
2025 · Ibrahim, Lujain, Akbulut, Canfer, et al. · arXiv (Cornell University) · 8
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Measuring and Mitigating (Over)reliance to Build Human-Compatible AI
2026 · Lujain Ibrahim, Katherine M. Collins, et al. · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · 4
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Thinking beyond the anthropomorphic paradigm benefits LLM research
2026 · Lujain Ibrahim, Myra Cheng · Proceedings of the conference - Association for Computational Linguistics. Meeting · 4
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Promising Topics for US–China Dialogues on AI Risks and Governance
2025 · Saad Siddiqui, Lujain Ibrahim, et al. · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · 4
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What Counts as AI Sycophancy? A Taxonomy and Expert Survey of a Fragmented Construct
2026 · Ye, Meryl, Ibrahim, Lujain, et al. · arXiv (Cornell University) · 1
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Sycophantic AI makes human interaction feel more effortful and less satisfying over time
2026 · Ibrahim, Lujain, Hafner, Franziska Sofia, et al. · arXiv (Cornell University) · 1
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Verbalizing LLMs' Assumptions About the User to Calibrate Expectations and Reduce Sycophancy
2026 · Myra Cheng, Sunny Yu, et al. · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · 1
Verbalizing LLMs' assumptions to explain and control sycophancy
2026 · Cheng, Myra, Sieh, Isabel, et al. · arXiv (Cornell University) · 1
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Evaluating Language Models for Harmful Manipulation
2026 · Akbulut, Canfer, Elasmar, Rasmi, et al. · arXiv (Cornell University) · 1
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Characterizing and modeling harms from interactions with design patterns in AI interfaces
2024 · Ibrahim, Lujain, Rocher, Luc, et al. · arXiv (Cornell University) · 1
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Do Explanations Improve the Quality of AI-assisted Human Decisions? An Algorithm-in-the-Loop Analysis of Factual & Counterfactual Explanations
2023 · Lujain Ibrahim, Mohammad M. Ghassemi, et al. · Adaptive Agents and Multi-Agents Systems · 1
The Patient Is Always Right? Evaluating Sycophancy in Medical Diagnosis with Graded Patient Beliefs
2026 · Manoranjan, Viswonathan, Mock, Andrea, et al. · arXiv (Cornell University)
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AI manipulation is context-dependent
2026 · Canfer Akbulut, Abhishek Roy, et al. · Research Square
Tailored to you: longitudinal effects of personalising language models
2026 · Akbulut, Canfer, Breuch, Justine, et al. · arXiv (Cornell University)
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LLMs as Oracles: Reliance on LLMs for Subjective Personal Questions
2026 · Cheng, Myra, Ibrahim, Lujain, et al. · arXiv (Cornell University)
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Mitigating AI sycophancy's interpersonal impacts
2026 · Cinoo Lee, Anonymous, et al. · OSF Preprints (OSF Preprints)
Warning labels shift perceptions of sycophantic AI, but not its influence
2026 · Ibrahim, Lujain, Cheng, Myra, et al. · arXiv (Cornell University)
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Thinking beyond the anthropomorphic paradigm benefits LLM research
2026 · Association for Computational Linguistics 2026, Cheng, Myra, et al. · Underline Science Inc.
Offloading Score: Measuring AI Reliance Through Counterfactual Workflows
2026 · Padmakumar, Vishakh, Ibrahim, Lujain, et al. · arXiv (Cornell University)
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Works count: 35
Citation count: 248
H-index: 8
I10-index: 6
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