64 citations · 99 across the 8 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020★ 21 cited
GMAT: Global Memory Augmentation for Transformers
Ankit Gupta, Jonathan Berant
Transformer-based models have become ubiquitous in natural language processing thanks to their large capacity, innate parallelism and high performance. The contextualizing componen…
cs.CL2020
Injecting Numerical Reasoning Skills into Language Models
Mor Geva, Ankit Gupta, Jonathan Berant
Large pre-trained language models (LMs) are known to encode substantial amounts of linguistic information. However, high-level reasoning skills, such as numerical reasoning, are di…
cs.CL2020★ 5 cited
Break It Down: A Question Understanding Benchmark
Tomer Wolfson, Mor Geva, Ankit Gupta +4
Understanding natural language questions entails the ability to break down a question into the requisite steps for computing its answer. In this work, we introduce a Question Decom…