activity
20172026
most citedOn the Opportunities and Risks of Foundation Models

2.3k citations · 2.9k across the 59 of their papers we have counts for

collaborators
Showing 2026Show all

5 papers · 1 filter

cs.CL2026

Latent Taxonomies: How Property Induction Develops in Language Model Pre-training

Jan Sobotka, Ekaterina Goliakova, Marcin Detyniecki +2

When told that robins have sesamoid bones, people are far more prone to extend the property to sparrows than to whales. This behavior, called category-based property induction, is…

cs.AI2026

Do LLMs Game Formalization? Evaluating Faithfulness in Logical Reasoning

Kyuhee Kim, Auguste Poiroux, Antoine Bosselut

Formal verification guarantees proof validity but not formalization faithfulness. For natural-language logical reasoning, where models construct axiom systems from scratch without…

q-bio.NC2026

Large Language Models Align with the Human Brain during Creative Thinking

Mete Ismayilzada, Simone A. Luchini, Abdulkadir Gokce +5

Creative thinking is a fundamental aspect of human cognition, and divergent thinking-the capacity to generate novel and varied ideas-is widely regarded as its core generative engin…

cs.CL2026

CresOWLve: Benchmarking Creative Problem-Solving Over Real-World Knowledge

Mete Ismayilzada, Renqing Cuomao, Daniil Yurshevich +3

Creative problem-solving requires combining multiple cognitive abilities, including logical reasoning, lateral thinking, analogy-making, and commonsense knowledge, to discover insi…

cs.CY2026

AI Meets Mathematics Education: A Case Study on Supporting an Instructor in a Large Mathematics Class with Context-Aware AI

Jérémy Barghorn, Anna Sotnikova, Sacha Friedli +1

Large-enrollment university courses face persistent challenges in providing timely and scalable instructional support. While generative AI holds promise, its effective use depends…