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cs.CL2025
Anthropocentric bias in language model evaluation
Raphaël Millière, Charles Rathkopf
Evaluating the cognitive capacities of large language models (LLMs) requires overcoming not only anthropomorphic but also anthropocentric biases. This article identifies two types…
cs.CL2025
The Vector Grounding Problem
Dimitri Coelho Mollo, Raphaël Millière
Large language models (LLMs) produce seemingly meaningful outputs, yet they are trained on text alone without direct interaction with the world. This leads to a modern variant of t…
cs.CL2025
LLMs as Models for Analogical Reasoning
Sam Musker, Alex Duchnowski, Raphaël Millière +1
Analogical reasoning -- the capacity to identify and map structural relationships between different domains -- is fundamental to human cognition and learning. Recent studies have s…