Can Cognitive Neuroscience inform Neuro-Symbolic Inference Models?Download PDF

Published: 27 May 2021, Last Modified: 24 May 2023NSNLI OralReaders: Everyone
Keywords: Cognitive neuroscience, Human subject research, Cognitive architecture, Neural networks architecture
TL;DR: Our understanding of humans responding to inference tasks suggests we may need to incorporate specific biases in neuro-symbolic model architectures
Abstract: The use of neuro-symbolic methods to supplement the performance of deep learning based natural language inference models has witnessed a resurgence. In this work, we review three sets of recent results in human cognition experiments -- in natural language comprehension, in natural language inference, and in computer program comprehension - a field bearing similarities to natural language. In light of these three works, we discuss the broader role cognitive neuroscience can play in informing the design of neuro-symbolic inference model architectures for language.
Track: Positional paper
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