bidaf
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Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.
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May 31, 2023 - Python
Important paper implementations for Question Answering using PyTorch
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Dec 29, 2020 - Jupyter Notebook
Bidirectional Attention Flow for Machine Comprehension implemented in Keras 2
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Nov 21, 2022 - Python
Machine Reading Comprehension in Tensorflow
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Jul 14, 2019 - Python
Question Answering System using BiDAF Model on SQuAD v2.0
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Sep 2, 2020 - Python
Machine Comprehension using Squad and Triviqa Data sets
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Dec 11, 2017 - Jupyter Notebook
Multiple Sentences Bi-directional Attention Flow (Multi-BiDAF) network is a model designed to fit the BiDAF model of Seo et al. (2017) for the Multi-RC dataset. This implementation is built on the AllenNLP library.
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Sep 5, 2018 - Python
Implementation of the machine comprehension model in our ACL 2019 paper: Augmenting Neural Networks with First-order Logic.
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Nov 3, 2020 - Python
ML Projects and Experience in Industry and Academia.
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Dec 13, 2023
BI-DIRECTIONAL ATTENTION FLOW FOR MACHINE COMPREHENSION
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Mar 25, 2019 - Python
State of the art of Neural Question Answering using PyTorch.
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May 3, 2024 - Python
Bi-Directional Attention Flow (BiDAF) question answering model enhanced by multi-layer convolutional neural network character embeddings.
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Jan 28, 2020 - Python
Question answering on the SQuAD dataset, for NLP class at UNIBO
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Feb 4, 2021 - Jupyter Notebook
Answering a query about a given context paragraph using a model based on recurrent neural networks and attention.
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May 3, 2024 - Python
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