3 papers
cs.LG2026
Latent Structure of Affective Representations in Large Language Models
Benjamin J. Choi, Melanie Weber
The geometric structure of latent representations in large language models (LLMs) is an active area of research, driven in part by its implications for model transparency and AI sa…
cs.LG2025
Position: Beyond Euclidean -- Foundation Models Should Embrace Non-Euclidean Geometries
Neil He, Jiahong Liu, Buze Zhang +6
In the era of foundation models and Large Language Models (LLMs), Euclidean space has been the de facto geometric setting for machine learning architectures. However, recent litera…
cs.CG2025
Towards Non-Euclidean Foundation Models: Advancing AI Beyond Euclidean Frameworks
Menglin Yang, Yifei Zhang, Jialin Chen +2
In the era of foundation models and Large Language Models (LLMs), Euclidean space is the de facto geometric setting of our machine learning architectures. However, recent literatur…