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Shivangi Mahto

2 accepted papers

2021

Multi-timescale Representation Learning in LSTM Language Models

ICLR 2021poster

Language models must capture statistical dependencies between words at timescales ranging from very short to very long. Earlier work has demonstrated that dependencies in natural language tend to decay with distance between words according to a power law. However, it is unclear how this knowledge ca…

Cited by 35SourcePDFScholar
2020

Interpretable multi-timescale models for predicting fMRI responses to continuous natural speech

NeurIPS 2020poster

Natural language contains information at multiple timescales. 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). However, th…

Cited by 49SourcePDFScholar