1 citations · 1 across the 3 of their papers we have counts for
4 papers
AI Models Can Predict and Collaboratively Modulate Human Memory Search
Eric Lacosse, Mariana Duarte, Graham Todd +2
Large language models (LLMs) exhibit unprecedented natural language generation and many text-based problem-solving capabilities. Indeed, in many language-based tasks, for example r…
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…
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…
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…