5 papers
Independent-Component-Based Encoding Models of Brain Activity During Story Comprehension
Kamya Hari, Taha Binhuraib, Jin Li +2
Encoding models provide a powerful framework for linking continuous stimulus features to neural activity; however, traditional voxelwise approaches are limited by measurement noise…
LITcoder: A General-Purpose Library for Building and Comparing Encoding Models
Taha Binhuraib, Ruimin Gao, Anna A. Ivanova
We introduce LITcoder, an open-source library for building and benchmarking neural encoding models. Designed as a flexible backend, LITcoder provides standardized tools for alignin…
How Do LLMs Use Their Depth?
Akshat Gupta, Jay Yeung, Gopala Anumanchipalli +1
Growing evidence suggests that large language models do not use their depth uniformly, yet we still lack a fine-grained understanding of their layer-wise prediction dynamics. In th…
What does it mean to understand language?
Colton Casto, Anna Ivanova, Evelina Fedorenko +1
Language understanding entails not just extracting the surface-level meaning of the linguistic input, but constructing rich mental models of the situation it describes. Here we pro…
Log Probabilities Are a Reliable Estimate of Semantic Plausibility in Base and Instruction-Tuned Language Models
Carina Kauf, Emmanuele Chersoni, Alessandro Lenci +2
Semantic plausibility (e.g. knowing that "the actor won the award" is more likely than "the actor won the battle") serves as an effective proxy for general world knowledge. Languag…