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This paper discusses the effectiveness of various text processing techniques,their combinations, and encodings to achieve a reduction of complexity and sizein a given text corpus. The simplified text corpus is sent to BERT (or similartransformer based models) for question and answering and can produce morerelevant responses to user queries. This paper takes a scientific approach todetermine the benefits and effectiveness of various techniques and concludes abest-fit combination that produces a statistically significant improvement inaccuracy.

Techniques to Improve Q&A Accuracy with Transformer-based models on Large Complex Documents