3 papers
cs.AI2026
SCRIBE: Scalable Contextual Representations of Interpretable Brain-Grounded Semantics
Camila Kolling, Omer Moussa, Emin Çelik +1
Understanding how the human brain constructs meaning from real-world language remains a fundamental challenge, as semantics depend on context that varies in natural settings. To en…
cs.AI2026
Decomposing Brain-LLM Alignment with Interpretable Semantic Representations
Camila Kolling, Mariya Toneva
Large language models (LLMs) predict neural responses during naturalistic language comprehension, but the linguistic information underlying this brain alignment remains difficult t…
cs.LG2025
Large Language Models as Model Organisms for Human Associative Learning
Camila Kolling, Vy Ai Vo, Mariya Toneva
Associative learning--forming links between co-occurring items--is fundamental to human cognition, reshaping internal representations in complex ways. Testing hypotheses on how rep…