Ranked list fusion and re-ranking with pre-trained transformers for ARQMath lab

This paper elaborates on our submission to the ARQMath track at CLEF 2021. For our submission this year we use a collection of methods to retrieve and re-rank the answers in Math Stack Exchange in addition to our two-stage model which was comparable to the best model last year in terms of NDCG'. We also provide a detailed analysis of what the transformers are learning and why is it hard to train a math language model using transformers. This year's submission to Task-1 includes summarizing long question-answer pairs to augment and index documents, using byte-pair encoding to tokenize formula and then re-rank them, and finally important keywords extraction from posts. Using an ensemble of these methods our approach shows a 20% improvement than our ARQMath'2020 Task-1 submission.