Interpreting recurrent and attention-based neural models: a case study on natural language inference

R Ghaeini, XZ Fern, P Tadepalli - arXiv preprint arXiv:1808.03894, 2018 - arxiv.org
Deep learning models have achieved remarkable success in natural language inference
(NLI) tasks. While these models are widely explored, they are hard to interpret and it is often …
被引用次数：111 相关文章

Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference

R Ghaeini, XZ Fern, P Tadepalli - arXiv e-prints, 2018 - ui.adsabs.harvard.edu
Deep learning models have achieved remarkable success in natural language inference
(NLI) tasks. While these models are widely explored, they are hard to interpret and it is often …

Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference

R Ghaeini, X Fern, P Tadepalli - Proceedings of the 2018 …, 2018 - aclanthology.org
Deep learning models have achieved remarkable success in natural language inference
(NLI) tasks. While these models are widely explored, they are hard to interpret and it is often …
[PDF] researchgate.net

[PDF][PDF] Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference

R Ghaeini, XZ Fern, P Tadepalli - researchgate.net
Deep learning models have achieved remarkable success in natural language inference
(NLI) tasks. While these models are widely explored, they are hard to interpret and it is often …