2 citations · 6 across the 17 of their papers we have counts for
4 papers · 1 filter
The World According to LLMs: How Geographic Origin Influences LLMs' Entity Deduction Capabilities
Harsh Nishant Lalai, Raj Sanjay Shah, Jiaxin Pei +3
Large Language Models (LLMs) have been extensively tuned to mitigate explicit biases, yet they often exhibit subtle implicit biases rooted in their pre-training data. Rather than d…
A Neural Network Model of Complementary Learning Systems: Pattern Separation and Completion for Continual Learning
James P Jun, Vijay Marupudi, Raj Sanjay Shah +1
Learning new information without forgetting prior knowledge is central to human intelligence. In contrast, neural network models suffer from catastrophic forgetting: a significant…
Modeling Understanding of Story-Based Analogies Using Large Language Models
Kalit Inani, Keshav Kabra, Vijay Marupudi +1
Recent advancements in Large Language Models (LLMs) have brought them closer to matching human cognition across a variety of tasks. How well do these models align with human perfor…
The potential -- and the pitfalls -- of using pre-trained language models as cognitive science theories
Raj Sanjay Shah, Sashank Varma
Many studies have evaluated the cognitive alignment of Pre-trained Language Models (PLMs), i.e., their correspondence to adult performance across a range of cognitive domains. Rece…