5 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…
Perturbation-based Regional Interpretability through Subtraction Mapping (PRISM): naming-error dissociations in language models and post-stroke aphasia
Xiang Guan, Roger D. Newman-Norlund, Yong Yang +8
Mechanistic interpretability of large language models lacks spatially resolved, falsifiable tools for testing whether internal components are specialized for distinct cognitive ope…
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…
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…
Contrastive Diffusion Guidance for Spatial Inverse Problems
Sattwik Basu, Chaitanya Amballa, Zhongweiyang Xu +3
We consider a class of inverse problems characterized by forward operators that are partially specified, non-smooth, and non-differentiable. Although generative inverse solvers hav…