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Found 7 papers, 3 papers with code
Multi-Level Gazetteer-Free Geocoding
We present a multi-level geocoding model (MLG) that learns to associate texts to geographic coordinates.
Explaining black box text modules in natural language with language models
Here, we ask whether we can automatically obtain natural language explanations for black box text modules.
Self-supervised models of audio effectively explain human cortical responses to speech
Overall, these results show that self-supervised models effectively capture the hierarchy of information relevant to different stages of speech processing in human cortex.
Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech
To understand how the human brain represents this information, one approach is to build encoding models that predict fMRI responses to natural language using representations extracted from neural network language models (LMs).
Spatial Language Representation with Multi-Level Geocoding
We present a multi-level geocoding model (MLG) that learns to associate texts to geographic locations.
Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network
In this work, we explore the delayed-RNN, which is a single-layer RNN that has a delay between the input and output.
Incorporating Context into Language Encoding Models for fMRI
By varying the amount of context used in the models and providing the models with distorted context, we show that this improvement is due to a combination of better word embeddings learned by the LSTM language model and contextual information.
