Reading Comprehension: Question Answering Systems

Related lectures (19)

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Explores question answering systems, reading comprehension models, and the challenges in achieving accurate responses.

Explores challenges in question answering systems and solutions, including fine-tuning and open-domain retrieval.

Explores deep learning for question answering, analyzing neural networks and model robustness to noise.

Introduces classical language models, their applications, and foundational concepts like count-based modeling and evaluation metrics.

Teaches students how to read research articles actively and efficiently in social sciences, emphasizing engaging with the argument and evidence.

Explores formal grammars, parsing algorithms, CYK algorithm efficiency, and syntactic correctness in Natural Language Processing.

Delves into BERT pretraining for transformers, discussing its applications in NLP tasks.

Focuses on the key elements of an Instructional Design Document, covering scope, delivery, objectives, materials, stakeholders, and outline.

Covers contextual representations in NLP, focusing on ELMO and BERT architectures and their applications in various tasks.