5 papers
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…
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…
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…
How Do Transformers Learn Variable Binding in Symbolic Programs?
Yiwei Wu, Atticus Geiger, Raphaël Millière
Variable binding -- the ability to associate variables with values -- is fundamental to symbolic computation and cognition. Although classical architectures typically implement var…
Are LLMs Good Cryptic Crossword Solvers?
Abdelrahman Sadallah, Daria Kotova, Ekaterina Kochmar
Cryptic crosswords are puzzles that rely not only on general knowledge but also on the solver's ability to manipulate language on different levels and deal with various types of wo…