I recently graduated with a Master’s degree in Computational Linguistics from the University of Washington, where I was advised by Shane Steinert-Threlkeld. I currently work with Saloni Dash and Aylin Caliskan at UW’s Information School on reasoning and AI bias.

Previously, I worked as a Generative AI Analyst at NVIDIA, where I worked on tooling and quality monitoring for LLM annotation projects. Before that, I completed undergraduate degrees in Computer Science and Philosophy at Sorbonne Université (previously known as Université Paris-Sorbonne, Paris IV and Université Pierre et Marie Curie, Paris VI), and in English at Université Sorbonne Nouvelle.

I’m broadly interested in

• how language interacts with other cognitive processes (such as semantic cognition, generalization and reasoning) in humans and language models
• how AI systems shape, mediate, and reproduce social and cultural information
• methodological and philosophical questions about how knowledge is produced and evaluated (in general but particularly in AI research)

In my free time, I enjoy reading, watching films, dancing, and learning to knit!

Publications

• Saloni Dash, Amélie Reymond, Emma S. Spiro, Aylin Caliskan. 2025. Persona-Assigned Large Language Models Exhibit Human-Like Motivated Reasoning. Presented at the SocialSim Workshop at COLM 2025 arXiv:2506.20020 [cs.AI]
• Roberto Ceraolo, Dmitrii Kharlapenko, Ahmad Khan, Amélie Reymond, Punya Syon Pandey, Rada Mihalcea, Bernhard Schölkopf, Mrinmaya Sachan, Zhijing Jin. 2024. Analyzing Human Questioning Behavior and Causal Curiosity through Natural Queries. To appear in IJCNLP–AACL 2025 Findings. arXiv:2405.20318 [cs.CL]
• Amélie Reymond, Shane Steinert-Threlkeld. 2023. mSCAN: A Dataset for Multilingual Compositional Generalization Evaluation. In Proceedings of the GenBench Workshop at EMNLP 2023
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