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CogNLP-Sheffield at CMCL 2021 Shared Task: Blending Cognitively Inspired Features with Transformer-based Language Models for Predicting Eye Tracking Patterns
The CogNLP-Sheffield submissions to the CMCL 2021 Shared Task examine the value of a variety of cognitively and linguistically inspired features for predicting eye tracking patterns, as both standalone model inputs and as supplements to contextual word embeddings (XLNet).
We Need to Talk About Classification Evaluation Metrics in NLP
In Natural Language Processing (NLP) classification tasks such as topic categorisation and sentiment analysis, model generalizability is generally measured with standard metrics such as Accuracy, F-Measure, or AUC-ROC.
In Factuality: Efficient Integration of Relevant Facts for Visual Question Answering
Visual Question Answering (VQA) methods aim at leveraging visual input to answer questions that may require complex reasoning over entities.
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