Open Domain Question Answering

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Table of contents

1 Internship Presentation
1.1 Problem formulation
1.2 Piaf project
1.3 Internship objectives
2 Background
2.1 Open Domain Question Answering
2.1.1 Traditional Architectures
2.1.2 Modern OpenQA systems
2.1.3 Evaluation Metrics
2.2 Initial status of the project Piaf
3 Sparse Methods
3.1 Exact term matching
3.2 Theoretical background
3.3 Implementation
3.4 Results
4 Neural Language Models
4.1 Transformers
4.1.1 The encoder layer
4.1.2 The decoder layer
4.2 BERT
4.3 BERT for text ranking task
4.4 State of the art
4.4.1 Multi stage re-rankers
4.4.2 Dense retrievers
5 Datasets
5.1 French QA datasets
5.2 Text ranking dataset creation
5.3 Dataset Analysis
5.4 Data split
6 Methodology and implementation
6.1 BERT based model
6.2 Embeddings extraction
6.3 Classification Approach
6.4 Pairwise Approach
6.5 Complementary scoring
6.6 Fine-tuning the complete model
6.7 Long Documents Ranking
7 Results and discussion
7.1 Experimental setup
7.2 Evaluation Metrics
7.3 Results
7.4 Discussion
Conclusion