101 citations · 147 across the 6 of their papers we have counts for
Showing 2018 · cs.CLShow all
3 papers · 2 filters
cs.CL2018★ 8 cited
Analyzing Compositionality-Sensitivity of NLI Models
Yixin Nie, Yicheng Wang, Mohit Bansal
Success in natural language inference (NLI) should require a model to understand both lexical and compositional semantics. However, through adversarial evaluation, we find that sev…
cs.CL2018★ 14 cited
Commonsense for Generative Multi-Hop Question Answering Tasks
Lisa Bauer, Yicheng Wang, Mohit Bansal
Reading comprehension QA tasks have seen a recent surge in popularity, yet most works have focused on fact-finding extractive QA. We instead focus on a more challenging multi-hop g…
cs.CL2018★ 20 cited
Robust Machine Comprehension Models via Adversarial Training
Yicheng Wang, Mohit Bansal
It is shown that many published models for the Stanford Question Answering Dataset (Rajpurkar et al., 2016) lack robustness, suffering an over 50% decrease in F1 score during adver…