52 citations · 59 across the 2 of their papers we have counts for
5 papers
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal +53
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of auto…
Leveraging Visual Question Answering to Improve Text-to-Image Synthesis
Stanislav Frolov, Shailza Jolly, Jörn Hees +1
Generating images from textual descriptions has recently attracted a lot of interest. While current models can generate photo-realistic images of individual objects such as birds a…
P NP, at least in Visual Question Answering
Shailza Jolly, Sebastian Palacio, Joachim Folz +3
In recent years, progress in the Visual Question Answering (VQA) field has largely been driven by public challenges and large datasets. One of the most widely-used of these is the…
The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA
Shailza Jolly, Sandro Pezzelle, Tassilo Klein +2
We introduce MASSES, a simple evaluation metric for the task of Visual Question Answering (VQA). In its standard form, the VQA task is operationalized as follows: Given an image an…
How do Convolutional Neural Networks Learn Design?
Shailza Jolly, Brian Kenji Iwana, Ryohei Kuroki +1
In this paper, we aim to understand the design principles in book cover images which are carefully crafted by experts. Book covers are designed in a unique way, specific to genres…