4 citations · 7 across the 9 of their papers we have counts for
9 papers
Lesioned Multimodal Language Models Reproduce Aphasic Picture-Naming Patterns
Yong Yang, Xiang Guan, Sophie Arheix-Parras +7
Aphasia following stroke commonly produces systematic naming errors with characteristic profiles, but whether general-purpose language models not designed for clinical simulation c…
Recovering Lesion Parameters from Aphasic Picture Naming Error Profiles in Large Language Models
Yong Yang, Roger Newman-Norlund, Xiang Guan +10
Interpretability methods for large language models (LLMs) describe internal state but do not directly test whether that state is causally sufficient to produce the observed behavio…
Topological inference on brain networks with application to lesion symptom mapping
Yuan Wang, Jian Yin, Nicholas Riccardi +3
Persistent homology (PH) characterizes the shape of brain networks through persistence features. Group comparison of persistence features from brain networks can be challenging as…
Stroke Lesions as a Rosetta Stone for Language Model Interpretability
Julius Fridriksson, Roger D. Newman-Norlund, Saeed Ahmadi +10
Large language models (LLMs) have achieved remarkable capabilities, yet methods to verify which model components are truly necessary for language function remain limited. Current i…
Multifaceted neural representation of words in naturalistic language
Xuan Yang, Chuanji Gao, Cheng Xiao +2
Understanding how the brain represents the multifaceted properties of words in context is essential for explaining the neural architecture of human language. Here, we combine large…
Model Selection with Regression and Representational Similarity Analysis for Linear and Nonlinear Data
Chuanji Gao, Gang Chen, Svetlana V. Shinkareva +1
In cognitive psychology and neuroscience, adjudicating between competing theoretical models is a common methodological challenge. Researchers often rely on either first-order direc…
Topological inference on brain networks across subtypes of post-stroke aphasia
Yuan Wang, Jian Yin, Rutvik H. Desai
Persistent homology (PH) characterizes the shape of brain networks through the persistence features. Group comparison of persistence features from brain networks can be challenging…
The Two Word Test: A Semantic Benchmark for Large Language Models
Nicholas Riccardi, Rutvik H. Desai
Large Language Models (LLMs) have shown remarkable abilities recently, including passing advanced professional exams and demanding benchmark tests. This performance has led many to…
Network-based Statistics Distinguish Anomic and Broca Aphasia
Xingpei Zhao, Nicholas Riccardi, Rutvik H. Desai +3
Aphasia is a speech-language impairment commonly caused by damage to the left hemisphere. Due to the complexity of speech-language processing, the neural mechanisms that underpin v…