Description:
Learn about machine reading with neural networks in this comprehensive lecture from CMU's Neural Networks for NLP course. Explore various machine reading datasets, methods for encoding context and multi-hop reasoning, and important caveats about dataset biases. Dive into topics such as attention models, span selection, question decomposition, and retrieval-based question answering. Examine real-world examples from Daily Mail and natural questions datasets, and understand the challenges of adversarial examples and symbolic reasoning in machine reading tasks. Gain insights into the latest techniques for improving neural network performance in natural language processing and question answering systems.
Neural Nets for NLP 2021 - Machine Reading with Neural Nets
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#Computer Science
#Artificial Intelligence
#Neural Networks
#Natural Language Processing (NLP)
#Humanities
#Language Learning
#Reading Comprehension
#Machine Learning
#Language Models