3 papers
cs.AI2026
Representational Curvature Modulates Behavioral Uncertainty in Large Language Models
Jack King, Evelina Fedorenko, Eghbal A. Hosseini
In autoregressive large language models (LLMs), temporal straightening offers an account of how the next-token prediction objective shapes representations. Models learn to progress…
cs.AI2026
Emergence of Phonemic, Syntactic, and Semantic Representations in Artificial Neural Networks
Pierre Orhan, Pablo Diego-Simón, Emmnanuel Chemla +3
During language acquisition, children successively learn to categorize phonemes, identify words, and combine them with syntax to form new meaning. While the development of this beh…
cs.CL2025
Probing Syntax in Large Language Models: Successes and Remaining Challenges
Pablo J. Diego-Simón, Emmanuel Chemla, Jean-Rémi King +1
The syntactic structures of sentences can be readily read-out from the activations of large language models (LLMs). However, the ``structural probes'' that have been developed to r…