32 citations · 161 across the 38 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.CL2023
Uncertainty Guided Global Memory Improves Multi-Hop Question Answering
Alsu Sagirova, Mikhail Burtsev
Transformers have become the gold standard for many natural language processing tasks and, in particular, for multi-hop question answering (MHQA). This task includes processing a l…
cs.CL2023★ 19 cited
Scaling Transformer to 1M tokens and beyond with RMT
Aydar Bulatov, Yuri Kuratov, Yermek Kapushev +1
A major limitation for the broader scope of problems solvable by transformers is the quadratic scaling of computational complexity with input size. In this study, we investigate th…