activity
20172021
most citedComparing Attention-based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading Comprehension

2 citations · 4 across the 7 of their papers we have counts for

collaborators
Showing 2018Show all

2 papers · 1 filter

cs.CL2018★ 1 cited

Sequence-to-Sequence Models for Data-to-Text Natural Language Generation: Word- vs. Character-based Processing and Output Diversity

Glorianna Jagfeld, Sabrina Jenne, Ngoc Thang Vu

We present a comparison of word-based and character-based sequence-to-sequence models for data-to-text natural language generation, which generate natural language descriptions for…

cs.CL2018★ 2 cited

Comparing Attention-based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading Comprehension

Matthias Blohm, Glorianna Jagfeld, Ekta Sood +2

We propose a machine reading comprehension model based on the compare-aggregate framework with two-staged attention that achieves state-of-the-art results on the MovieQA question a…