Deep Learning and Synthetic Media. - Raphaël Millière (CoRR, 2022)

Adversarial Attacks on Image Generation With Made-Up Words. - Raphaël Millière (CoRR, 2022)

The Vector Grounding Problem. - Dimitri Coelho Mollo; Raphaël Millière (CoRR, 2023)

In-Context Learning in Large Language Models: A Neuroscience-inspired Analysis of Representations. - Safoora Yousefi; Leo Betthauser; Hosein Hasanbeig; Akanksha Saran; Raphaël Millière; Ida Momennejad (CoRR, 2023)

The Alignment Problem in Context. - Raphaël Millière (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

A Philosophical Introduction to Language Models - Part I: Continuity With Classic Debates. - Raphaël Millière; Cameron Buckner (CoRR, 2024)

A Philosophical Introduction to Language Models - Part II: The Way Forward. - Raphaël Millière; Cameron Buckner (CoRR, 2024)

Philosophy of Cognitive Science in the Age of Deep Learning. - Raphaël Millière (CoRR, 2024)

Semantic Structure-Mapping in LLM and Human Analogical Reasoning. - Sam Musker; Alex Duchnowski; Raphaël Millière; Ellie Pavlick (CoRR, 2024)

Anthropocentric bias and the possibility of artificial cognition. - Raphaël Millière; Charles Rathkopf (CoRR, 2024)

Language Models as Models of Language. - Raphaël Millière (CoRR, 2024)

How Do Transformers Learn Variable Binding in Symbolic Programs? - Yiwei Wu; Atticus Geiger; Raphaël Millière (CoRR, 2025)

Normative Conflicts and Shallow AI Alignment. - Raphaël Millière (CoRR, 2025)