2 citations · 6 across the 17 of their papers we have counts for
9 papers · 1 filter
On the use of foundation models in cognitive science
Raj Sanjay Shah, Alex Warstadt, Michael Frank +1
A host of recent studies have evaluated the cognitive and developmental alignment of Foundation Models (FMs). These investigations include evaluations of their correspondence to ad…
Human-Like Anaphor Resolution in Large Language Models
Keane Zhang, Varshini Chinta, Raj Sanjay Shah +1
Anaphors are expressions that refer to other expressions, called antecedents. The process of connecting the two is called resolution. Cognitive science has identified multiple fact…
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…
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…
Development of Cognitive Intelligence in Pre-trained Language Models
Raj Sanjay Shah, Khushi Bhardwaj, Sashank Varma
Recent studies show evidence for emergent cognitive abilities in Large Pre-trained Language Models (PLMs). The increasing cognitive alignment of these models has made them candidat…
Incremental Comprehension of Garden-Path Sentences by Large Language Models: Semantic Interpretation, Syntactic Re-Analysis, and Attention
Andrew Li, Xianle Feng, Siddhant Narang +4
When reading temporarily ambiguous garden-path sentences, misinterpretations sometimes linger past the point of disambiguation. This phenomenon has traditionally been studied in ps…
Towards a Path Dependent Account of Category Fluency
David Heineman, Reba Koenen, Sashank Varma
Category fluency is a widely studied cognitive phenomenon, yet two conflicting accounts have been proposed as the underlying retrieval mechanism -- an optimal foraging process deli…
Pre-training LLMs using human-like development data corpus
Khushi Bhardwaj, Raj Sanjay Shah, Sashank Varma
Pre-trained Large Language Models (LLMs) have shown success in a diverse set of language inference and understanding tasks. The pre-training stage of LLMs looks at a large corpus o…