3 papers
cs.LG2026
Emergent Causal-Geometric Dynamics Across Depth in Large Language Models
Shahar Haim, Daniel C McNamee
Geometric analyses of large language model (LLM) representations reveal structured variation across depth but remain fundamentally correlational with respect to token prediction fo…
q-bio.NC2026
Integrative neurocybernetic modeling in the era of large-scale neuroscience
Il Memming Park, Ayesha Vermani, Gonzalo G. de Polavieja +11
Large-scale neuroscience is generating rich datasets across animals, brain areas and behavioral contexts, yet our modeling efforts remains fragmented across isolated experiments. W…
cs.AI2026
Emerging Human-like Strategies for Semantic Memory Foraging in Large Language Models
Eric Lacosse, Mariana Duarte, Peter M. Todd +1
Both humans and Large Language Models (LLMs) store a vast repository of semantic memories. In humans, efficient and strategic access to this memory store is a critical foundation f…